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Data Management and Governance Practices (2017)

Chapter: Appendix A - Survey Questionnaires and Responses

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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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Suggested Citation:"Appendix A - Survey Questionnaires and Responses." National Academies of Sciences, Engineering, and Medicine. 2017. Data Management and Governance Practices. Washington, DC: The National Academies Press. doi: 10.17226/24777.
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A-1 Appendix A Survey Questionnaires and Responses phase 1 Survey Dear Members of AASHTO Subcommittee on Data/AASHTO SCOP Committee and Agency Representatives: The transportation Research Board (TRB) is preparing a synthesis that will summarize current practices related to the topic Data Maintenance Practices. This is being done for the National Cooperative Highway Research Program (NCHRP), under the sponsorship of the American Association of State Highway and transportation Officials (AASHTO), in cooperation with the Federal Highway Administration (FHWA). Transportation agencies are increasingly collecting large amounts of data for use in various business areas, such as planning, operations, construction, maintenance, and resource allocation. This questionnaire is part of the effort in NCHRP Synthesis Topic 47-05 to gather information on data management practices at transportation agencies. The results of this synthesis project will show how transportation agencies currently govern, manage, integrate, and share data in the interest of sharing best practices among trans- portation agencies. The survey is divided into two phases: • Phase 1 (this questionnaire): Screening survey to gather information that will be used to customize Phase 2 questions to pertain only to those data management practices and policies of responding organizations. The intent is to make the Phase 2 survey as short and specific as possible. • Phase 2: Tailored follow-up survey that will be launched upon analyzing the responses to Phase 1. Your cooperation in completing the questionnaire will ensure the success of this effort. If you are not the appropriate person at your organization to complete this questionnaire, please forward it to the correct person. Please complete and submit this survey by May 13, 2016. We estimate that it should take approximately 10–15 minutes to complete. It could take longer if the participant needs to contact other individuals in his/her organizations to help answer some of the questions. If you have any questions, please contact our Principal Investigator, Dr. Nasir Gharaibeh, at (979) 845-3362 or ngharaibeh@civil.tamu.edu. Thank you very much for your time and expertise. Please enter your contact information below. NCHRP will e-mail you a link to the online report when it is completed. First Name*: _________________________________________________ Last Name*: _________________________________________________ Title*: ______________________________________________________ Agency/Organization*: _________________________________________ E-mail Address*: ______________________________________________ Phone Number*: ______________________________________________ Phase 1 Survey 1) Does your agency have a designated data governance board/council? Data Governance Board/Council: Group that institutes policies and oversees activities regarding data governance throughout the organization. Data governance is defined as “the execution and enforcement of authority over the management of data assets and the performance of data functions” (NCHRP Report 666, 2010).* Responses of DOTs M Yes – 8 responses M No – 19 responses M In Development – 16 responses

A-2 Responses of Local Agencies M Yes – 1 response M No – 18 responses M In Development – No response 2) If you answered “yes” or “in development” to Question 1, please describe this board/council briefly (e.g., group name, staff positions/titles, contact person): Responses of DOTs Response 1 – “We have Data Governance Board, which will include the CIO and Data Management Coordinator for strategic leadership. It provides leadership and strategic direction for a broad range of governance issues including but not limited to internal controls, data governance, administrative policy, data practices, and records management. Data Domain Stewards are for tactical leadership. The agency has identified nine data domains and assigned a domain steward to each. There are over 100 subject areas organized by domain. Examples of subject area would include: grant data, bicycle data, and roadway condition data. The Domain Steward is usually an office director.” Response 2 – “Through an effort under the Program and Special Studies Area, a unify database is under development to consolidate pavement, traffic, and road inventory data, as a first phase. In a second and third phase, all data develop and/or acquire by the agency, will be feed into the system for a complete Roads and transportation Database Management System.” Response 3 – “An informal assembly of business owners and asset stewards across bureaus.” Response 4 – “At one point, Agency had the Data Governance Council, no longer active. The Asset Data Management Committee (ADMC) was formed to represent primarily linear assets. Policy direction for that committee is provided by Asset Management Exec. Committee. What current governance bodies there are through committees could be restructured or incorporated into a new system. Agency is currently developing a Strategic Data Business Plan (SDBP) for the agency which is expected to include governance.” Response 5 – “We are in the infancy stages of a data governance council. The intended positions are: Data Governance Board Chair, Data Coordinator, Data Steward, Data Management Coordinator, Metadata Specialist, Data Warehouse Architect, Business Analyst, Database Administrator, Data Architect.” Response 6 – “Agency has a Geospatial Data Governance Board focusing on geospatial data. The Board is run by agency’s Geospatial Information Office.” Response 7 – “Agency has structured governance policies for the core data programs: traffic, road network, and crash. The road network entails road centerlines, LRS, and roadway features. We currently are converting our GIS over to ESRI’s Roads and Highways, which will provide a more well defined and efficient governance. The DOT as a whole developed a strawman data governance policy and an accompanying data governance procedure manual as part of our asset management program. Since completing that effort, the Department had a major reorganization - creating a separate Information Systems and Services Division (ISSD). ISSD will take the lead on data governance. There have been substantive IT infrastructure, personnel, and operational policies to deal with during the reorganization, but the data governance policy and procedures are now being addressed. Probably will be the end of the year before they get completed. I could share the strawman documents if there is interest.” Response 8 – “Data Governance Working Group.” Response 9 – “Reliable Organized Accurate Data Sharing (ROADS) Steering Committee.” Response 10 – “Enterprise Data Sharing and Storage Committee. Comprised of business areas (Maintenance, traffic Operations, Safety, Planning) and Office of Information Technology (OIT) personnel. Generally comprised of the data managers of the business areas along with enterprise solutions personnel in OIT.” Response 11 – “The agency’s Enterprise Information Governance Group is composed of division directors who represent the various organizational business activities, the Knowledge Strategist, and IT specialists in Information Management. The prime focal point of the group is on establish- ing and reviewing agency policies regarding data and information management. There are also other specialized data governance groups - Formation of an asset management governance group is underway and there is also a Data Warehouse Governance group.” Response 12 – “The Council is a joint entity of the Information Technology Agency and the Depart- ment of transportation. It is made up of mid-career professional and technical unionized workforce members from each transportation program area and information technology program area. Members are designated by their program area to vet proposals with colleagues within the program

A-3 area and speak to the interests of the program area with respect to proposals submitted for clearance review.” Response 13 – “Name: Data Governance Committee Purpose: To discuss and coordinate efforts that deal with collecting, creating, maintaining and analyzing data across the agency. This includes data awareness, availability, accessibility, maintenance, security, storage, and usage. Members: Various Division Heads throughout the Department.” Response 14 – “There are various efforts with our IT department, and as part of Asset Management contracts” Response 15 – “Data Governance Board – GIS Manager, Chair – Data SME – Asset Mang – DMV – Document Management” Response 16 – “Data governance is managed by agency’s Policy Division. This was rolled out a week ago and I am not familiar with all the staff positions/titles.” Response 17 – “We currently have a policy document outlining data collection and coordination along with internal rules within the GIS office for data policies.” Response 18 – “The Chief Information Officer and his staff are responsible for ensuring that the business goals and initiatives for agency have a strategy that is sound in technology, ultimately becoming a beneficial and operational business process and decision support facility for agency staff.” Response 19 – “Agency is currently in the process of developing a Data Governance model; the current model is distributed across various divisions and is informally maintained via corporate culture. A formal approach to Governance is being approached in steps with the initial efforts originating with the IT division identifying standardized processes and procedures for both internal and external data consumers.” Response 20 – “The board is called the ‘Drive Team.’ Made up of directors from around the Department, the Drive Team is charged with implementation of the Department’s Asset Management business model and serves as the advisory council to the executive management team, primary decision-making body for Data Standards, major data/information initiatives and oversight ongoing ‘portfolio’ of IT application development projects and investments.” Response 21 – “This council consists of 6 second or third line DOT supervisors representing the major data areas of the department. It also includes 2 IT representatives. There is no staff—this is a policy board.” Response 22 – “The Department has an Asset Management and Performance Strategies (AMPS) section within the Bureau of Planning whose responsibility it is to work with all Data Managers throughout the agency to develop governance policies for agency data needs” Response 23 – “We have a weekly Data Governance Working Group that consists of data stewards from our various divisions. We also have a Data Governance Executive Committee that meets every month and they are updated on the activities of the DG Working Group and they will also approve or disapprove any issues that the DG Working Group has. The DG Exec Committee sets the priorities for the DG Working Group.” Response of Local Agency Response 1 – “IT Department maintains and archives agency data, no protocols specific to trans- portation data. Supports COOP function.” 3) Does your agency have designated data coordinators? Data Coordinator: Committee or individual that coordinates the organization, sharing, access, and use of multiple data sets within a business area (e.g., asset management, safety).* Responses of DOTs M Yes – 26 responses M No – 6 responses M In Development – 11 responses Responses of Local Agencies M Yes – 5 responses M No – 12 responses M In Development – 2 responses

A-4 4) If you answered “yes” or “in development” to question 3, please describe these coordinators briefly (e.g., business areas, staff positions/titles, contact persons): 1. 2. 3. Responses of DOTs Response 1 – “Subject Area Stewards are responsible for the data within their purview. They coordinate with other Subject Area Stewards as needed to facilitate sharing of data, reduction of duplication and increasing access to data.” Response 2 – “Asset management coordinator is responsible for gathering all necessary data sets, and keeping them updated in the State Planning and Operations Database (SPOD).” Response 3 – “The agency has officially two coordinators in terms of data interchange and exchange for other state agencies, municipalities, the private sector, and the federal government. These are the GIS Coordinator and the HPMS Coordinator. The GIS Coordinator a primarily task is to oversees data exchange between entities and keep external data up to date. The HPMS Coordinator primarily task is to coordinate data compilation, management and processing to meet FHWA report- ing requirements.” Response 4 – “The MIS department is coordinating a data warehouse concept. Weekly meetings with major data areas coordinate dashboards, data audits, and development.” Response 5 – “Engineering, Planning and Asset Management” Response 6 – “Data Management and Statistical Support Section, Safety Data, and Data Manager positions exist. Primarily this covers asset condition data, traffic data, and safety data.” Response 7 – “Data Coordinators do exist for many program areas with a variety of titles and classifications. There is not a formal designation. People acting as coordinators may not have consistent roles, responsibilities, or provide the same level of effort and completeness.” Response 8 – “Data management is still spread throughout the agency until we establish the data council, which could up to take 5 years to fully implement. For now, SHA has fund managers and asset owners who manage their data. 20% of physical asset data is in an asset data warehouse; not all reported metrics are in the data set. Asset Data Stewards are spread throughout the agency in various district offices; examples of assets include rumble strips, signs, park and ride, highway system, guard rails.” Response 9 – “Under the Asset Management and Performance Management efforts, Caltrans is developing a more systematic method for data coordination.” Response 10 – “One data governance area of need is to identify the data systems and subject matter experts with each business area. There is interest in creating a data registry for this. Again, we have a strawman data registry completed, but undoubtedly will be reformatted before rolling out to the Department.” Response 11 – “We have coordinators for the Highway Performance Monitoring System and for Safety data.” Response 12 – “Each Functional Group (business area) within the agency has a designated Enter- prise Data Steward, Data Stewards and Data Custodians. This list of persons (330+) is fairly well established, but is changing during the development phase of the project.” Response 13 – “1 GIS Coordinator and 1 Roadway Inventory Coordinator per Agency district.” Response 14 – “The Enterprise Data Branch of OIT are responsible for ensuring business data is available at an organizational level via transportation Enterprise Database (TED). Data managers in each business area coordinate, as needed, for clarity of purpose when using data that originates in another business area.” Response 15 – “Some areas of the department have well-formed data stewardship and coordination of data access roles - the transportation Data and GIS Office (crash, roadway and traffic data) and Accounting and financial Services. Other areas either do not have or are in the process of growing such roles.” Response 16 – “We have system administrators for each automated business system who administer user requests for access to the application and data within the application. They train users and do data QA/QC for the system they administer. Also have data stewards who oversee matters such as OLTP Data, time series warehouse data, data reporting quick marts, data integration among systems, and business intelligence among multiple systems within a knowledge domain and in some cases across multiple domains. The information technology agency roles are concerned with regular backups of data, disaster recovery strategy, and classification of data from the lenses of security (confidential vs. public) and criticality (i.e., service level agreements for outages).”

A-5 Response 17 – “The Data Governance committee serves as the top-level data coordination council. In addition, there is an Enterprise GIS Data committee that consists of individual data coordinators from various business areas across the agency such as: Planning, environmental, bridge, Maintenance, System Information, Right of Way etc.” Response 18 – “We have some staff within our GIS section that coordinate data sets and sharing with other divisions and work units within the DOT.” Response 19 – “We have data stewards for many data sets but [their] responsibilities are not well defined.” Response 20 – “The Office of Technical Services is the main repository for transportation Asset data because of our business responsibility of Locational Referencing System (LRS) and Geographical Information Systems (GIS). Our Office is also responsible for updating enterprise data sets to the most current year LRS. We also coordinate the TAM activities for the department in terms of data collection, standards, working with the various businesses to ensure data integrity as well as access and distribution of data.” Response 21 – “Data sharing is coordinated between agency’s Information Technology Division and agency’s Business Data Owners/Business Stakeholders. The Business Data Owners represent the business units, i.e., Local Assistance, Maintenance, transportation and Mobility Planning, and traffic and Engineering, Structure and bridge, Infrastructure Investment, etc.” Response 22 – “Through the process of developing the EGIS (Enterprise-wide GIS) program, several committees were formed to develop collaboration and integrate individual data silos into the EGIS program. This process is on-going.” Response 23 – “They are in business areas.” Response 24 – “Data Coordinators for highway, pavement, traffic, photolog, and highway performance monitoring are in the Bureau of State Highway Programs. Managers of these programs are responsible for implementing policy and data life cycle.” Response 25 – “Data owners/managers responsible for certain datasets.” Response 26 – “Agency has historically practiced a data steward model that ranged from formal to informal depending upon the division. The role is not dedicated at 100% FTE but instead is practiced by an individual serving as a designated point of contact who manages data maintenance, data distribution, etc. according to the division’s business model. Department IT is currently attempt- ing to formalize a GIS stewards model across divisions as part of a recent effort to centralize GIS information.” Response 27 – “We have a group of what we call ‘system administrators’ that oversee individual information systems (databases and associated data, coordination, training, software, and processes). These system administrators convene monthly to share updates and ask/answer questions about upcoming changes and issues. Typically, these system administrators act as go-to people for users and help to disseminate knowledge and understanding to users and others affected by information system changes.” Response 28 – “Same AMPS Section—one administrator position, two civil engineers, one business system analyst, and one more being developed.” Response 29 – “We have data stewards in every Division that will coordinate the sharing and permissions of their data.” Responses of Local Agencies Response 1 – “IT Department maintains and archives agency data, no protocols specific to trans- portation data. GIS department publishes multiple data sets from various sources, many without metadata.” Response 2 – “Title: Data Management Specialist” Response 3 – “We do not have designated data coordinators, but we do have a de-facto data coordinator. The head of the Long-Range transportation Planning Group has been making data organization decisions.” Response 4 – “No formal designation of specific staff, distributed among several.” Response 5 – “GIS Program Manager” Response 6 – “Not necessarily ‘designated’ but we have a GIS staff person who organizes/shares/ accesses data sets.” Response 7 – “Not ‘in development’ so much as ‘partial.’ Principal Analyst (survey respondent) is project manager for CMAP’s Data and Information Services project: oversees acquisition of public datasets for and archiving of obsolete datasets for our internal data warehouse.” Response 8 – “Responsible for posting agency-developed datasets on public data portal. We also maintain a Regional transportation Data Archive and probe data.”

A-6 5) Does your agency have a document that describes its current data governance model? Responses of DOTs M Yes – 11 responses M No – 20 responses M In Development – 12 responses Responses of Local Agencies M Yes – No response M No – 19 responses M In Development – No response 6) If you answered “yes” to Question 5, would you be willing to provide the research team with a copy of your agency’s data governance document for use as an example? Responses of DOTs M Yes – 12 responses M No – 4 responses Responses of Local Agencies No response 7) Please answer the questions in the table below. Please check all that apply. Data Warehouse/Mart: A data warehouse is a unified repository of current and historical data obtained from multiple sources. A data mart is a scaled-down version of a data warehouse. Data Steward: Individual who is accountable for assuring the quality of a specific data set, ensuring compliance with data rules and regulations, defining metadata, and relaying the appropriate use of the data. Data archiving: The process of moving electronic data that is no longer actively used to a separate storage device for long-term retention. (NCHRP Report 814)* Data Set What data in your agency are maintained in data warehouses or marts (as opposed to disparate files and databases)? What data in your agency have designated stewards? What data in your agency are archived systematically to retain historical information? Roadway inventory (e.g., location, classification, geometrics) Crash data Traffic monitoring data (e.g., speed, volume) Travel modeling data (e.g., household surveys, origin- destination) Highway Performance Monitoring System (HPMS) Pavement inventory and condition data Pavement work history data Bridge inventory and condition data

A-7 Responses of DOTs Response 1 – Data that have designated stewards: Roadway inventory, crash data, traffic monitor- ing data, HPMS, pavement inventory and condition data, bridge inventory and condition data, transportation improvement programs data, contracts/procurement data, project construction data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, transportation improvement programs data, contracts/procurement data, project construction data, financial data. Response 2 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, financial data, others. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and con- dition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data, others. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data, others. Contracts/procurement data (e.g., bid tabs) Project construction data (e.g., cost/payments, schedule, material acceptance testing, as-built plans) Real estate data (e.g., property acquisition, agency-owned parcels) Financial data (e.g., current and historical revenues, expenditures, budgets) Others Inventory and condition data for other assets (e.g., traffic signs, signals, drainage assets) Transportation improvement programs data Environmental impact and compliance data Project design and materials data (e.g., design plans, structural design, mix design) Data Set What data in your agency are maintained in data warehouses or marts (as opposed to disparate files and databases)? What data in your agency have designated stewards? What data in your agency are archived systematically to retain historical information? Bridge work history data

A-8 Response 3 – Data maintained in data warehouses or marts: pavement inventory and condition data, bridge inventory and condition data, transportation improvement programs data, project construction data, financial data. Data that have designated stewards: crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, Inventory and condition data for other assets, real estate data, financial data. Data that are archived systematically to retain historical records: traffic monitoring data, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, project design and materials data, project construction data. Response 4 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, contracts/procurement data, project construction data, financial data. Data that have designated stewards: Roadway inventory, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/procurement data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and con- dition data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/procurement data, project construction data, financial data. Response 5 – Data maintained in data warehouses or marts: Roadway inventory, HPMS, pavement inventory and condition data, bridge inventory and condition data, bridge work history data, contracts/ procurement data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, contracts/procurement data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, bridge work history data, contracts/procurement data, financial data, contracts/procurement data, financial data. Response 6 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that have designated stewards: Roadway, crash data, traffic monitoring data, Travel model- ing data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, project design and materials data, contracts/ procurement data, project construction data, real estate data, financial data. Response 7 – Data that have designated stewards: Roadway inventory, crash data, Travel modeling data, HPMS, pavement inventory and condition data. bridge inventory and condition data, trans- portation improvement programs. Data that are archived systematically to retain, historical records: Roadway inventory, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, financial data Response 8 – Data that have designated stewards: traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data,

A-9 Response 9 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, financial data Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/ procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, project design and materials data, contracts/ procurement data, financial data. Response 10 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inven- tory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Response 11 – Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Response 12 – Data that have designated stewards: Roadway inventory, crash data, traffic monitor- ing data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compli- ance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pave- ment work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construc- tion data, real estate data, financial data. Response 13 – Data maintained in data warehouses or marts: crash data Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance

A-10 data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Response 14 – Data maintained in data warehouses or marts: crash data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and con- dition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, project design and materials data, contracts/procurement data, project construction data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, transportation improvement programs, project design and materials data, contracts/procurement data, project construction data, financial data. Response 15 – Data maintained in data warehouses or marts: HPMS, bridge inventory and condition data, bridge work history data, transportation improvement programs, contracts/procurement data, real estate data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inven- tory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Response 16 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, environmental impact and compliance data, contracts/procurement data, project construction data, financial data. Response 17 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inven- tory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Response 18 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and

A-11 compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transporta- tion improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inven- tory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, financial data. Response 19 – Data maintained in data warehouses or marts: Roadway inventory, crash data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs data. Data that have designated stewards: Roadway inventory, crash data, HPMS, pavement inventory and condition data Response 20 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construc- tion data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, project design and materials data, contracts/ procurement data, project construction data, financial data. Response 21 – Data maintained in data warehouses or marts: Roadway inventory, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs data, financial data, others Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement, programs data, financial data, others. Data that are archived systematically to retain historical records: Roadway inventory, traffic moni- toring data, HPMS, pavement inventory and condition data, Inventory and condition data for other assets, transportation improvement programs data. Response 22 – Data maintained in data warehouses or marts: Roadway inventory, crash data, bridge inventory and condition data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs data, envi- ronmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data. Data that are archived systematically to retain historical records: traffic monitoring data, HPMS, project design and materials data, project construction data. Response 23 – Data maintained in data warehouses or marts: Roadway inventory, traffic monitoring data, bridge inventory and condition data, Inventory and condition data for other assets. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data.

A-12 Data that are archived systematically to retain historical records: Roadway inventory, traffic monitor- ing data, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, project design and materials data, project construction data. Response 24 – Data maintained in data warehouses or marts: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, bridge work history data, transportation improvement programs data, environmental impact and compliance data, contracts/procurement data, project construction data, financial data, others. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data, others. Data that are archived systematically to retain historical records: Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data, others. Response 25 – Data maintained in data warehouses or marts: transportation improvement programs data, financial data, others. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inven- tory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Response 26 – Data maintained in data warehouses or marts: Roadway inventory, traffic monitoring data, HPMS, bridge inventory and condition data, bridge work history data, contracts/procurement data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/procurement data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, traffic moni- toring data, HPMS, pavement inventory and condition data, pavement work history data, project design and materials data, contracts/procurement data, project construction data, financial data. Response 27 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, transportation improvement programs data, contracts/procurement data, project construction data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: crash data, financial data. Response 28 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, HPMS, bridge inventory and condition data, transportation improvement programs data, project construction data, financial data. Data that have designated stewards: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, contracts/procurement data, project construction data, real estate data, financial data.

A-13 Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, contracts/procurement data, project construction data, real estate data, financial data. Response 29 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data. Response 30 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, pavement inventory and condition data, bridge inventory and condition data, environmental impact and compliance data, contracts/procurement data, project construction data, real estate data, financial data. Data that have designated stewards: Roadway inventory, crash data, pavement inventory and condition data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: crash data, pavement inventory and condition data, environmental impact and compliance data, contracts/procurement data, project construction data, real estate data, financial data. Response 31 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, others. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and con- dition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data, others. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, others. Response 32 – Data maintained in data warehouses or marts: Roadway inventory, traffic monitor- ing data, HPMS, bridge inventory and condition data, Inventory and condition data for other assets, project design and materials data, project construction data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, project construction data, real estate data, others. Data that are archived systematically to retain historical records: Roadway inventory, traffic moni- toring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and con- dition data for other assets, project design and materials data, contracts/procurement data, project construction data, financial data. Response 33 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project con- struction data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inven- tory and condition data for other assets, transportation improvement programs data, environmental

A-14 impact and compliance data, project design and materials data, contracts/procurement data, project construction data. Response 34 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs data Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs data. Response 35 – Data maintained in data warehouses or marts: Roadway inventory, bridge inventory and condition data, transportation improvement programs data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data, others. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inven- tory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data, others. Response 36 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/procurement data, project construction data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transporta- tion improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Response 37 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, HPMS, bridge inventory and condition data, project design and materials data, project construction data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and con- dition data, bridge work history data, transportation improvement programs data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Response 38 – Data maintained in data warehouses or marts: Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets,

A-15 transportation improvement programs data, contracts/procurement data, project construction data, real estate data, financial data, others. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, contracts/procurement data, project construction data, real estate data, financial data, others. Data that are archived systematically to retain historical records: Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data, others. Response 39 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traf- fic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, others. Data that have designated stewards: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, others. Data that are archived systematically to retain historical records: Roadway inventory, HPMS. Response 40 – Data maintained in data warehouses or marts: crash data, HPMS, bridge inventory and condition data, bridge work history data, transportation improvement programs data, contracts/ procurement data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, envi- ronmental impact and compliance data, project design and materials data, contracts/procurement data, financial data. Data that are archived systematically to retain historical records: crash data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Response 41 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic, monitoring data, bridge inventory and condition data, environmental impact and compliance data, project design and materials data, project construction data, real estate data, financial data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modelling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, project design and materials data, contracts/procurement data, project construction data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, environmental impact and compliance data, project design and materials data, project construction data, real estate data, financial data. Response 42 – Data maintained in data warehouses or marts: Roadway inventory, traffic monitoring data, pavement inventory and condition data, pavement work history data. Data that are archived systematically to retain historical records: Roadway inventory, traffic moni- toring data, pavement inventory and condition data, pavement work history data. Response 43 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, project construction data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, project design and materials data, contracts/ procurement data, project construction data, real estate data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, project design and materials data, contracts/procurement data, project construction data.

A-16 Responses of Local Agencies Response 1 – Data maintained in data warehouses or marts: transportation improvement programs data, financial data. Data that are archived systematically to retain historical records: transportation improvement programs data. Response 2 – Data maintained in data warehouses or marts: Roadway inventory, transportation improvement programs data, real estate data, financial data. Data that have designated stewards: Roadway inventory, transportation improvement programs data, real estate data, financial data. Data that are archived systematically to retain historical records: Roadway inventory, pavement inventory and condition data, transportation improvement programs data, real estate data, financial data. Response 3 – Data maintained in data warehouses or marts: contracts/procurement data, real estate data, financial data. Data that have designated stewards: Travel modeling data, contracts/procurement data, real estate data, financial data. Data that are archived systematically to retain historical records: Travel modeling data, transportation improvement programs data, contracts/procurement data, real estate data, financial data. Response 4 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, pavement inventory and condition data, bridge inventory and condition data, transportation improvement programs data, others. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, pavement inventory and condition data, bridge inventory and condition data, transportation improvement programs data, others. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, pavement inventory and condition data, bridge inventory and condition data, transportation improvement programs data, others. Response 5 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs data, environmental impact and compliance data, contracts/procurement data. Data that have designated stewards: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, pavement inventory and condition data, pavement work history data, bridge inven- tory and condition data, bridge work history data, contracts/procurement data. Response 6 – Data that have designated stewards: transportation improvement programs data, financial data, others. Response 7 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, HPMS, bridge inventory and condition data, contracts/procurement data. Data that have designated stewards: Travel modeling data, pavement inventory and condition data, transportation improvement programs data, financial data. Data that are archived systematically to retain historical records: Travel modeling data, pavement inventory and condition data, transportation improvement programs data, contracts/procurement data, financial data. Response 8 – Data maintained in data warehouses or marts: traffic monitoring data, others. Data that are archived systematically to retain historical records: Travel modeling data. Response 9 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, transportation improvement programs data. Data that are archived systematically to retain historical records: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, transportation improvement programs data, environ- mental impact and compliance data. Response 10 – Data that are archived systematically to retain historical records: crash data. Response 11 – Data maintained in data warehouses or marts: Travel modelling data. Data that have designated stewards: Travel modelling data. Data that are archived systematically to retain historical records: Travel modelling data. Response 12 – Data maintained in data warehouses or marts: Travel modelling data.

A-17 Response 13 – Data maintained in data warehouses or marts: crash data, project design and materials data. Data that have designated stewards: Travel modeling data, Inventory and condition data for other assets, project design and materials data. Data that are archived systematically to retain historical records: crash data, project design and materials data. Response 14 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets. Response 15 – Data maintained in data warehouses or marts: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data. Data that have designated stewards: Roadway inventory, crash data, Travel modeling data, trans- portation improvement programs data, environmental impact and compliance data. Response 16 – Data maintained in data warehouses or marts: Roadway inventory, HPMS, pavement inventory and condition data, bridge inventory and condition data, bridge work history data. Data that have designated stewards: crash data, traffic monitoring data, Travel modeling data, transportation improvement programs data. Response 17 – Data maintained in data warehouses or marts: Travel modeling data, transportation improvement programs data, environmental impact and compliance data. Response 18 – Data maintained in data warehouses or marts: others. Data that have designated stewards: Travel modeling data, transportation improvement programs data, contracts/procurement data, financial data. Data that are archived systematically to retain historical records: Travel modeling data, trans- portation improvement programs data, contracts/procurement data, financial data. Response 19 – Data maintained in data warehouses or marts: Roadway inventory, traffic monitoring data, Travel modeling data, Inventory and condition data for other assets, transportation improvement programs data, environmental impact and compliance data, contracts/procurement data, project con- struction data, real estate data, financial data. Data that are archived systematically to retain historical records: crash data, environmental impact and compliance data. 8) If you checked “others” in question 7, please describe these data. Responses of DOTs Response 1 – Historical Aerial Photographs of state from 1930 to 2007. Response 2 – Maintenance Management System with plan vs accomplishment, major activity amounts and costs, Consultant contract Administration for PE selections and cost. Response 3 – HR; Motor Carrier; Fleet Management System; Safety; Aggregate; Unstable Slopes (Landslides). Response 4 – Road Weather Information Systems (RWIS) is a major area for Agency. RWIS supports three primary areas: a) Winter weather maintenance decisions b) Seasonal weight restrictions— implementing and removing c) Travel decisions for the 511 traveler information systems. RWIS provides: a) Atmospheric conditions b) pavement surface conditions c) Soil temperature profiles d) Camera images, including nighttime images using infrared illuminators. With the exception of camera images (which are retained only for 24 hours), we archive and make available (publicly for most of the information, the one exception is pavement condition). Response 5 – The ARRA data reporting requirements (circa 2009) were fulfilled by building a warehouse environment for that program only. It is in process of being decommissioned as vendor version upgrades of the platforms for business intelligence necessitate migration of warehouses to new environments, and business needs for the data diminish to close to zero usage. Response 6 – All Public Roads LRS and City Limit/County Boundaries. Responses of Local Agencies Response 1 – GIS department publishes various datasets from multiple sources, many without metadata.

A-18 Response 2 – Cross-border estimated delay for passenger and commercial vehicles. Response 3 – Title VI/Env. Justice related data. Response 4 – Regional transportation Data Archive includes: incident and construction data. Probe Database includes: National Performance Measurement Research Dataset, additional HERE (Navteq) data, and license plate odometer readings. 9) Please enter any additional comments you may have in the space below: Responses of DOTs Response 1 – “In the agency there are a number of individual databases for finance, construction, design, contracts, environment, etc. But is only access is restrained.” Response 2 – “The Strategic Data Business Plan under development used a stakeholder input process and workshops to develop a common strategic data vision, goals and objectives for the agency. The current focus is on development of 1) a common ‘toolbox’ for achieving the goals and objectives and 2) an agency Baseline to help direct the development of strategies. For additional information contact Denise.” Response 3 – “HPMS data is archived by FHWA.” Response 4 – “Data Stewards and Data Custodians are actively being identified and designated at this time.” Response 5 – “Inventory and Conditions Data . . . includes a strong inventory of signals and a devel- oping inventory of signs and drainage assets. Pavement Inventory Data is close to being accessible via TED. Working on resolving LRS between pavement Data and TED.” Response 6 – “There are many stewards of the agency’s asset data and there is overlap between the various systems. Most of these systems were created as independent efforts and rarely include a full accounting of all assets in the subject area. There is no standard way of tying items together between systems. We do employ ECM solutions to house design plans, and we have an extensive investment in GIS data and tools. Many of the GIS data sets are spatial renditions of subsets of information from our tabular systems.” Response 7 – “I will forward an updated answer to questions 5 and 6, if my preliminary ‘No’ for question 5 turns out to be false upon further investigation with my colleagues.” Response 8 – “Data governance is a growing area of interest and concern for the agency. Within another year or so, we will likely have made much more progress in this area.” Response 9 – “We have one enterprise repository which is accessible via our transportation Infor- mation Mapping System (TIMS). We have over 85 datasets currently in the enterprise and a request for up to 150 that we are working towards. The data has been structured to allow for easy integration with other datasets and various systems; i.e., pavement management, maintenance management. All of this is supported on the back in by geospatial platforms and tools (ESRI). We utilize ESRI Roads and Highways to update our Roadway Network and then register the various datasets and perpetuate the changes.” Response 10 – “The department is currently developing a system to incorporate data from all of these various sources into a single viewing/retrieval/querying platform. Although this system is not complete, we have crossed the major hurdle of getting all of the various Bureaus and groups on board with the system.” Response 11 – “We have very little formal methods to even keep track of stewards as stewards, even though we know who is responsible for what. We have not formalized this. An ongoing dis- cussion about data retention is currently in play. We tend to hold on to lots of data that should be either archived or disposed of. Current retention policies have not been extended to electronic data, partially because we designed our systems assuming the data would always be there.” Responses of Local Agencies Response 1: “As an MPO we use the data collected by the State or municipalities. We do run the AQ advisory committee and are responsible for AQ related database.” Response 2: “Although as an MPO we use many of the data sources cited; we do not generate, maintain, or archive those copied files.” The Phase 1 survey is complete. Thank you for your participation!

A-19 phase 2 Survey Dear Participants: This questionnaire is the second phase of the survey being conducted as part of NCHRP Synthesis Topic 47-05 (Data Maintenance Practices). The questions in this survey were designed based on the results of Phase 1 survey. This synthesis project is being conducted for the National Cooperative Highway Research Program (NCHRP), under the sponsorship of the American Association of State Highway and transportation Officials (AASHTO), in cooperation with the Federal Highway Administration (FHWA). Your cooperation in completing the questionnaire will ensure the success of this effort. If you are not the appropriate person at your organization to complete this questionnaire, please forward it to the correct person. Please complete and submit this survey by May 13, 2016. We estimate that it should take approximately 15 minutes to complete. It could take longer if the participant needs to contact other individuals in his/her organizations to help answer some of the questions. If you have any questions, please contact our Principal Investigator, Dr. Nasir Gharaibeh, at (979) 845-3362 or ngharaibeh@civil.tamu.edu Thank you very much for your time and expertise. Please enter your contact information below. NCHRP will e-mail you a link to the online report when it is completed. First Name*: _________________________________________________ Last Name*: _________________________________________________ Title*: ______________________________________________________ Agency/Organization*: _________________________________________ E-mail Address*: ______________________________________________ Phone Number*: ______________________________________________ data Governance and Quality 1) To what extent do the following factors limit progress on instituting data governance in your agency? If other factors are applicable, please specify them in the entry boxes titled “Enter another option.” Factor Major Factor Minor Factor Not an Issue Other mission-related issues are more pressing Hard to justify the cost and effort Lack of resources Lack of staffing *Enter another option* *Enter another option* Responses of DOTs Response 1 – Major factor: Other mission-related issues are more pressing, lack of resources, lack of staffing. Minor factor: Hard to justify the cost and effort. Response 2 – Major factor: Lack of staffing. Minor factor: lack of resources and lack of com- munication. Not an issue: Other mission-related issues are more pressing and hard to justify the cost and effort. Response 3 – Major factor: Other mission-related issues are more pressing. Minor factor: Hard to justify the cost and effort, lack of resources and lack of staffing. Response 4 – Major factor: Other mission-related issues are more pressing, lack of resources and lack of staffing. Minor factor: Hard to justify the cost and effort. Response 5 – Major factor: Other mission-related issues are more pressing, cost and effort, lack of resources and lack of staffing. Minor factor: Hard to justify the cost and effort.

A-20 Response 6 – Major factor: Hard to justify the cost and effort, lack of staffing. Minor Factor: Other mission-related issues are more pressing, small community of data managers allows for simple communication. Not an Issue: Lack of staffing. Response 7 – Minor Factor: Other mission-related issues are more pressing. Response 8 – Major Factor: Other mission-related issues are more pressing, hard to justify the cost and effort, lack of resources, lack of staffing. Minor Factor: Lack of understanding. Response 9 – Major Factor: Other mission-related issues are more pressing, hard to justify the cost and effort, lack of understanding from Executive staff. Response 10 – Major Factor: Other mission-related issues are more pressing, lack of staffing. Minor Factor: Lack of resources. Not an Issue: Hard to justify the cost and effort. Response 11 – Major Factor: Other mission-related issues are more pressing, lack of staffing, lack of policies and procedures, lack of standards. Minor Factor: Lack of resources. Not an Issue: Hard to justify the cost and effort. Response 12 – Major Factor: Lack of resources. Minor Factor: Other mission-related issues are more pressing, lack of staffing. Not an Issue: Hard to justify the cost and effort. Response 13 – Major Factor: Other mission-related issues are more pressing. Minor Factor: Hard to justify the cost and effort, lack of resources, lack of staffing. Response 14 – Major Factor: Lack of resources, lack of staffing. Minor Factor: Other mission-related issues are more pressing. Not an Issue: Hard to justify the cost and effort. Response 15 – Major Factor: Other mission-related issues are more pressing, hard to justify the cost and effort, lack of resources and lack of staffing. Response 16 – Major Factor: Lack of resources, lack of staffing. Minor Factor: Other mission-related issues are more pressing, hard to justify the cost and effort. Response 17 – Not an Issue: Other mission-related issues are more pressing, hard to justify the cost and effort, lack of resources and lack of staffing. Response 18 – Major Factor: Other mission-related issues are more pressing, lack of resources, lack of staffing, Lack of understanding the magnitude of the data collected—number of datasets . . . and lack of communication. Minor Factor: Hard to justify the cost and effort. Response 19 – Major Factor: Other mission-related issues are more pressing, hard to justify the cost and effort, lack of resources. Minor Factor: Lack of staffing. Response 20 – Major Factor: Lack of staffing. Minor Factor: Lack of resources. Not an Issue: Other mission-related issues are more pressing, Hard to justify the cost and effort. Response 21 – Minor Factor: Other mission-related issues are more pressing, lack of resources, lack of staffing, Not an issue: Hard to justify the cost and effort. Response 22 – Major Factor: Other mission-related issues are more pressing. Minor Factor: Lack of resources, lack of staffing. Not an Issue: Hard to justify the cost and effort. Response 23 – Major Factor: Other mission-related issues are more pressing, lack of staffing, historical focus on projects, not underlying data. Minor Factor: Hard to justify the cost and effort, lack of resources. Response 24 – Major Factor: Lack of resources, lack of staffing, competing priorities (Asset Man- agement, Safety, IT), Development of an enterprise solution, IT resources are committed to other initiatives, Lack of understanding of technical needs (geospatial/data integration/mapping) and how they should be envisioned for the enterprise. Minor Factor: Other mission-related issues are more pressing, Hard to justify the cost and effort. Response 25 – Major Factor: Lack of resources, lack of staffing. Minor Factor: Other mission-related issues are more pressing, hard to justify the cost and effort. Response 26 – Major Factor: Lack of program lead and leadership instructions, Lack of formal governance policy and manuals. Minor Factor: Other mission-related issues are more pressing, Lack of resources, lack of staffing. Not an Issue: Hard to justify cost and effort. Response 27 – Major Factor: Other mission-related issues are more pressing, hard to justify the cost and effort, lack of resources, lack of staffing. Response 28 – Major Factor: Lack of resources, lack of staffing, lack of flexibility in communications on governance in IT, Siloed thinking. Minor Factor: Other mission-related issues are more pressing, hard to justify the cost and effort. Response 29 – Major Factor: Other mission-related issues are more pressing. Minor Factor: Lack of resources, lack of staffing. Not an Issue: Hard to justify the cost and effort. Response 30 – Major Factor: Lack of resources, lack of staffing. Minor Factor: Other mission-related issues are more pressing, hard to justify the cost and effort.

A-21 Response 31 – Major Factor: Other mission-related issues are more pressing. Minor Factor: Hard to justify the cost and effort, lack of resources, lack of staffing. Response 32 – Major Factor: Lack of resources, lack of staffing. Minor Factor: Other mission- related issues are more pressing. Not an Issue: Hard to justify the cost and effort, lack of resources, lack of staffing. Response 33 – Major Factor: Other mission-related issues are more pressing, lack of staffing, culture of separate “fiefdoms” (this matters FAR more than anything else). Minor Factor: Hard to justify the cost and effort, lack of resources. Responses of Local Agencies Response 1 – Major Factor: Hard to justify the cost and effort, lack of resources, lack of staffing. Minor Factor: Other mission-related issues are more pressing. Response 2 – Not an Issue: Other mission-related issues are more pressing, hard to justify the cost and effort, lack of resources, lack of staffing. Response 3 – Major Factor: Other mission-related issues are more pressing, lack of staffing. Not an Issue: Hard to justify the cost and effort, lack of resources. Response 4 – Major Factor: Lack of resources, lack of staffing. Minor Factor: Other mission-related issues are more pressing, hard to justify the cost and effort. Response 5 – Major Factor: Other mission-related issues are more pressing, hard to justify the cost and effort, lack of resources, lack of upper management support. Minor Factor: Lack of staffing. Response 6 – Major Factor: Hard to justify the cost and effort, lack of staffing. Minor Factor: Other mission-related issues are more pressing, lack of resources. Response 7 – Major Factor: Other mission-related issues are more pressing, lack of resources, lack of staffing. Minor Factor: Hard to justify the cost and effort. Response 8 – Major Factor: Other mission-related issues are more pressing, lack of resources, lack of staffing. Minor Factor: Hard to justify the cost and effort. Response 9 – Major Factor: Other mission-related issues are more pressing. Minor Factor: Lack of resources, lack of staffing. Response 10 – Major Factor: Hard to justify the cost and effort, lack of resources, lack of staffing. Minor Factor: Other mission-related issues are more pressing. Response 11 – Major Factor: Other mission-related issues are more pressing, hard to justify the cost and effort, lack of staffing. Minor Factor: Lack of resources. 2) To what extent are data quality elements evaluated in your agency? Data Quality Element Evaluated in All or Most Areas Evaluated in Some Areas Evaluated in a Few Areas Not Evaluated Accuracy (closeness between a data value and the real-world value that it represents) Completeness (absence of missing values in the dataset) Timeliness (how up-to-date the data are with respect to the task at hand) Relevancy (data are applicable and useful for the task at hand) Consistency (degree to which the data item is presented in the same format across agency) Accessibility (ability of authorized users to access the data) Access security (ability to restrict access to data to maintain security)

A-22 Responses of DOTs Response 1 – Evaluated in All or Most Areas: Accuracy. Evaluated in Some Areas: Completeness, Timeliness, Relevancy and Consistency. Evaluated in a Few Areas: Accessibility, Access security. Response 2 – Evaluated in All or Most Areas: Timeliness. Evaluated in Some Areas: Accuracy, Completeness, Relevancy, Access security. Evaluated in a Few Areas: Consistency, Accessibility. Response 3 – Evaluated in All or Most Areas: Accuracy, Completeness, Consistency. Evaluated in Some Areas: Timeliness, Relevancy, Accessibility, Access security. Response 4 – Evaluated in All or Most Areas: Accuracy, Access security. Evaluated in Some Areas: Completeness Timeliness, Relevancy, Consistency, Accessibility. Response 5 – Evaluated in All or Most Areas: Accessibility. Evaluated in Some Areas: Accuracy, Timeliness, Relevancy, Access security. Evaluated in a Few Areas: Completeness Consistency. Response 6 – Evaluated in All or Most Areas: Timeliness, Accessibility. Evaluated in Some Areas: Relevancy, Consistency. Evaluated in a Few Areas: Accuracy, Completeness, Access security. Response 7 – Evaluated in All or Most Areas: Access security. Evaluated in Some Areas: Accuracy, Completeness, Timeliness, Relevancy, Consistency, Accessibility. Response 8 – Evaluated in All or Most Areas: Accuracy, Completeness, Timeliness. Evaluated in Some Areas: Accessibility. Evaluated in a Few Areas: Relevancy, Consistency, Access security. Response 9 – Evaluated in All or Most Areas: Relevancy, Access security. Evaluated in Some Areas: Accuracy, Completeness, Timeliness, Accessibility. Evaluated in a Few Areas: Consistency. Response 10 – Evaluated in Some Areas: Accuracy, Completeness, Timeliness, Relevancy. Evaluated in a Few Areas: Consistency, Accessibility, Access security. Response 11 – Evaluated in Some Areas: Accuracy, Completeness, Timeliness, Relevancy, Acces- sibility, Access security. Evaluated in a Few Areas: Consistency. Response 12 – Evaluated in All or Most Areas: Completeness, Timeliness, Consistency, Accessibility, Access security. Evaluated in Some Areas: Accuracy, Relevancy. Response 13 – Evaluated in All or Most Areas: Accessibility, Access security. Evaluated in Some Areas: Accuracy, Completeness, Timeliness, Relevancy. Evaluated in a Few Areas: Consistency. Response 14 – Evaluated in All or Most Areas: Accuracy, Timeliness, Relevancy. Evaluated in Some Areas: Completeness, Consistency, Accessibility, Access security. Response 15 – Evaluated in Some Areas: Accuracy, Completeness Timeliness, Relevancy, Acces- sibility, Access security. Evaluated in a Few Areas: Consistency. Response 16 – Evaluated in All or Most Areas: Accuracy, Completeness, Access security. Evaluated in Some Areas: Timeliness, Relevancy, Consistency, Accessibility. Response 17 – Evaluated in Some Areas: Accuracy, Completeness, Timeliness, Relevancy, Con- sistency, Accessibility, Access security. Response 18 – Evaluated in All or Most Areas: Accuracy, Completeness, Timeliness, Relevancy, Consistency, Accessibility, Access security. Response 19 – Evaluated in All or Most Areas: Timeliness, Relevancy, Access security. Evaluated in Some Areas: Completeness, Accessibility. Evaluated in a Few Areas: Accuracy, Consistency. Response 20 – Evaluated in All or Most Areas: Completeness, Timeliness, Relevancy. Evaluated in Some Areas: Accuracy, Consistency, Accessibility, Access security. Response 21 – Evaluated in All or Most Areas: Accuracy, Completeness. Evaluated in Some Areas: Timeliness, Relevancy. Evaluated in a Few Areas: Accuracy, Consistency, Accessibility, Access security. Response 22 – Evaluated in All or Most Areas: Accuracy, Completeness, Timeliness, Relevancy, Consistency. Evaluated in Some Areas: Accessibility, Access security. Response 23 – Evaluated in All or Most Areas: Access security. Evaluated in Some Areas: Accuracy, Timeliness. Evaluated in a Few Areas: Completeness, Relevancy, Consistency, Accessibility. Response 24 – Evaluated in All or Most Areas: Completeness, Relevancy, Access security. Evaluated in Some Areas: Accuracy, Timeliness, Consistency. Evaluated in a Few Areas: Accessibility. Response 25 – Evaluated in All or Most Areas: Accuracy, Completeness, Timeliness, Accessibility, Access security. Evaluated in a Few Areas: Relevancy, Consistency. Response 26 – Evaluated in All or Most Areas: Accuracy, Completeness, Timeliness, Relevancy, Consistency, Accessibility, Access security. Response 27 – Evaluated in Some Areas: Accuracy, Timeliness, Accessibility, Access security. Evaluated in a Few Areas: Completeness, Relevancy, Consistency.

A-23 Response 28 – Evaluated in Some Areas: Accuracy, Completeness, Timeliness, Relevancy, Con- sistency, Accessibility, Access security. Response 29 – Evaluated in All or Most Areas: Relevancy, Consistency, Access security. Evaluated in Some Areas: Accuracy, Completeness, Timeliness, Accessibility. Response 30 – Evaluated in All or Most Areas: Relevancy, Access security. Evaluated in Some Areas: Timeliness. Evaluated in a Few Areas: Accuracy, Completeness, Consistency, Accessibility. Response 31 – Evaluated in All or Most Areas: Accuracy, Accessibility, Access security. Evaluated in Some Areas: Completeness, Timeliness, Consistency. Evaluated in a Few Areas: Relevancy. Response 32 – Evaluated in All or Most Areas: Accuracy, Completeness, Timeliness. Evaluated in Some Areas: Relevancy, Consistency, Accessibility, Access security. Response 33 – Evaluated in All or Most Areas: Accuracy, Completeness, Timeliness, Relevancy, Consistency, Accessibility, Access security. Response 34 – Evaluated in All or Most Areas: Accuracy, Completeness, Timeliness, Relevancy, Access security. Evaluated in Some Areas: Consistency, Accessibility. Responses of Local Agencies Response 1 – Evaluated in All or Most Areas: Relevancy, Accessibility. Evaluated in Some Areas: Evaluated in a Few Areas: Accuracy, Completeness, Timeliness, Consistency, Access security. Response 2 – Evaluated in All or Most Areas: Accuracy, Consistency. Evaluated in Some Areas: Completeness, Timeliness, Relevancy, Accessibility, Access security. Response 3 – Evaluated in All or Most Areas: Accuracy, Completeness, Timeliness, Relevancy, Consistency, Accessibility, Access security. Response 4 – Evaluated in All or Most Areas: Accuracy, Completeness, Timeliness, Relevancy, Consistency, Access security. Evaluated in Some Areas: Accessibility. Response 5 – Not Evaluated: Accuracy, Completeness, Timeliness, Relevancy, Consistency, Accessibility, Access security. Response 6 – Evaluated in All or Most Areas: Accuracy, Completeness. Evaluated in Some Areas: Timeliness, Relevancy, Access security. Evaluated in a Few Areas: Consistency, Accessibility. Response 7 – Evaluated in All or Most Areas: Accuracy, Completeness, Relevancy, Consistency, Accessibility. Evaluated in Some Areas: Timeliness, Access security. Response 8 – Evaluated in All or Most Areas: Timeliness, Relevancy, Accessibility. Evaluated in Some Areas: Accuracy, Completeness, Consistency, Access security. Response 9 – Evaluated in Some Areas: Timeliness, Accessibility. Evaluated in a Few Areas: Accuracy, Completeness, Relevancy, Consistency, Access security. Response 10 – Evaluated in All or Most Areas: Accuracy. Evaluated in Some Areas: Completeness. Evaluated in a Few Areas: Timeliness, Consistency. Not Evaluated: Accessibility, Access security Response 11 – Evaluated in Some Areas: Accuracy, Completeness Timeliness, Relevancy. Evaluated in a Few Areas: Consistency, Accessibility, Access security. data integration and Sharing 3) Which of these data sets are integrated in your agency to serve various business needs? Please check all that apply in the grid below. Example: Check the box at the intersection of Row A and Column B to indicate that roadway inventory (A) and crash data (B) are integrated.

A-24 Responses: Please see Appendix C. Comments of DOTs Response 1: “The other systems (the unchecked ones) often include LRS information as part of their attribution, but sometimes this information is incomplete and not associated with a date. This makes calculations between the state of the roadway at different time periods difficult. Differing levels of resolution also makes the data difficult to integrate.” Response 2: “Some of the integrated datasets are only partially integrated at this time.” Response 3: “Best guesses, not thoroughly vetted.” Response 4: “State System only J-used Enhanced Priority Formula System (EPFS) M-used WinCMPS.” Response 5: “I only marked above the diagonal because ‘integrated’ could be interpreted as primary flow direction, reverse flow direction, or both.” Response 6: “Our enterprise GIS datasets and Location References or unique identifiers provide us with at least one point of integration in every category listed. However, while some data is routinely integrated in systems such as a data warehouse, other datasets need to be linked to each other using a manual/custom process.” Response 7: “Details of integration beyond Items A through D and J are unknown to this reporter.” Response 8: “The format for this is very confusing. Also, we can relate data across data sets, but that doesn’t mean they are ‘integrated’ in the technical sense (in the same database).” Response 9: “Everything is linked via route ID and Measure, and location functions that can snap to the centerline. All these can be intersected or unioned. Not all of these are pre-intersected or pre-unioned.” Response 10: “I am assuming it is a given that certain datasets are integrated such as bridge Inventory/bridge Work History and contracts/financial. I did not take the time to confirm them all, but rather checked the disparate ones that I know are integrated.” Response 11: “All will be beneficial.” Comments of Local Agencies Response 1: “We have access to and maintain many of these datasets. However, none of those included above are wholly integrated beyond existing in the same file structure. They are very much silo-ed despite their obvious relationship to one another.” Response 2: “Most of these data sets are not owned/maintained by our agency and are therefore not applicable.” A B C D E F G H I J K L M N O P A B C D E F G H I J K L M N O P

A-25 4) What data sets would be beneficial for your agency to integrate? Please check all that apply in the grid below. Example: Check the box at the intersection of Row E and Column G to indicate that it would be beneficial for your agency to integrate pavement inventory and condition data (E) and bridge inventory and condition data (G). A B C D E F G H I J K L M N O P A B C D E F G H I J K L M N O P Responses: Please see Appendix C. Comments of DOTs Response 1: “The Agency is striving for presenting these datasets is a way that they can be used for analysis together by the end user. Our focus is not to integrate these datasets unless it is required by the transactional system and instead to rely on source systems to manage ancillary datasets and present them through other means for analytics.” Response 2: “We are currently working on tying all of our data system in to our roadway inventory.” Response 3: “I only marked above the diagonal because ‘integrated’ could be interpreted as primary flow direction, reverse flow direction, or both.” Response 4: “This is solely from my perspective (Items A-D, J). There are very likely other integra- tions that I’m missing that Agency would benefit from.” Response 5: “Again, this is confusing. We’re working on integrating roadway features inventories, changing our financial system, and extracting engineering features from construction into maintain- able asset inventories.” Response 6: “Take the converse set from #3, and that would be the start point. Somewhere in the diverse organization a DOT is, it would be beneficial.” Response 7: “It would be beneficial if all these data sets were integrated. Therefore, I did not bother to check all the boxes”

A-26 Comment of Local Agency Response 1: “Most of these data sets are not owned/maintained by our agency and are therefore not applicable.” 5) What location referencing methods are used in your agency? (Please check all that apply.) Route mile point: Distance from the beginning of the route. Route reference post: Distance and direction from a physical mile marker posted on the route in the field. Route street reference: Distance and direction on one street from another intersecting street. Multilevel linear referencing systems (MLLRS): Includes multiple linear referencing methods and transformation mechanism to a common one. Geographic coordinates: Geospatial coordinates such as latitude and longitude; or State plane coordinates. Data Set Route mile point Route reference post Link- node Route street reference Multileve l LRS Geographic coordinates Other or NA Roadway inventory (e.g., location, classification, geometrics) Crash data Traffic monitoring data (e.g., speed, volume) Travel modeling data (e.g., household surveys, origin- destination) Highway Performance Monitoring System (HPMS) Pavement inventory and condition data Pavement work history data Bridge inventory and condition data Bridge work history data Inventory and condition data for other assets (e.g., traffic signs, signals, drainage assets) Transportation improvement programs data Environmental impact and compliance data Contracts/procurement (e.g., bid tabs) Project construction data (e.g., cost/ payments, schedule, material acceptance testing, as-built plans)

A-27 Responses of DOTs Response 1 – Route mile point: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets. Route reference post: pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data. Route street reference: crash data. Geographic coordinates: Roadway inventory, crash data, traffic monitoring, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets. Response 2 – Route mile point: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, transportation improvement programs, project construction data. Route reference post: bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, contracts/procurement, project construction data. Link node: crash data Geographic coordinates: pavement inventory and condition data Response 3 – Route mile point: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs, environmental impact and com- pliance data. Geographic coordinates: crash data, Inventory and condition data for other assets. Response 4 – Route mile point: Roadway inventory, crash data, traffic monitoring data, HPMS, pave- ment inventory and condition data, pavement work history data, bridge inventory and condition data, inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data. Response 5 – Route mile point: roadway inventory, crash data, traffic monitoring data, travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/ procurement, project construction data. Route—street reference: HPMS Geographic coordinates: roadway inventory, crash data, traffic monitoring data, travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, inventory and condition data for other assets, environmental impact and compliance data, project construction data. Response 6 – Route mile point: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs. Geographic coordinates: crash data, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs. Other or NA: Travel modeling data, bridge work history data, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data. Response 7 – Route mile point: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data. Link node: Travel modeling data. Geographic coordinates: Roadway inventory, crash data, traffic monitoring data, pavement work history data, bridge inventory and condition data. Response 8 – Route mile point: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/ procurement, project construction data. Geographic coordinates: Roadway inventory, crash data, bridge inventory and condition data, Inventory and condition data for other assets. Other or NA: Travel modeling data, contracts/procurement, project construction data.

A-28 Response 9 – Route mile point: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, contracts/procurement. Route reference post: Travel modeling data, contracts/procurement. Link node: Roadway inventory, crash data, HPMS. Route street reference: Roadway inventory, crash data, Travel modeling data. Multilevel LRS: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condi- tion data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement. Geographic coordinates: Roadway inventory, HPMS, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement. Response 10 – Route mile point: Roadway inventory, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/ procurement, project construction data. Route reference post: pavement inventory and condition data, environmental impact and compliance data, contracts/procurement. Link–node: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets. Route street reference: environmental impact and compliance data. Geographic coordinates: pavement inventory and condition data, environmental impact and com- pliance data. Other or NA: contracts/procurement, project construction data. Response 11 – Route mile point: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improve- ment programs, contracts/procurement, project construction data. Link node: Travel modeling data. Route street reference: HPMS. Multilevel LRS: Roadway inventory: Geographic coordinates: Roadway inventory, crash data, Travel modeling data, pavement inventory and condition data, bridge inventory and condition data. Other or NA: Roadway inventory. Response 12 – Route mile point: Roadway inventory. Route reference post: Roadway inventory. Link node: Roadway inventory. Route street reference: Roadway inventory, HPMS. Multilevel LRS: Roadway inventory, HPMS. Geographic coordinates: HPMS. Response 13 – Route mile point: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improve- ment programs, environmental impact and compliance data. Route street reference: Roadway inventory, crash data, Travel modeling data. Multilevel LRS: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data. Geographic coordinates: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, trans- portation improvement programs, environmental impact and compliance data. Other or NA: contracts/procurement, project construction data.

A-29 Response 14 – Route mile point: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs, project construction data. Geographic coordinates: crash data, traffic monitoring data, pavement inventory and condition data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, project construction data. Other or NA: contracts/procurement. Response 15 – Route reference post: pavement inventory and condition data. Route street reference: crash data. Geographic coordinates: Roadway inventory, crash data, pavement inventory and condition data. Response 16 – Route mile point: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs, contracts/procurement. Route reference post: Roadway inventory, crash data, traffic monitoring data, bridge inventory and condition data, bridge work history data, project construction data. Multilevel LRS: Roadway inventory. Geographic coordinates: Roadway inventory, crash data, bridge inventory and condition data, bridge work history data, contracts/procurement. Other or NA: Travel modeling data, Inventory and condition data for other assets. Response 17 – Route mile point: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, contracts/procurement. Route reference post: pavement inventory and condition data, pavement work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data. Link node: crash data, traffic monitoring data, Travel modeling data. Geographic coordinates: crash data, bridge inventory and condition data, bridge work history data, environmental impact and compliance data. Response 18 – Route mile point: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, contracts/procurement. Link node: Travel modeling data. Multilevel LRS: crash data. Geographic coordinates: crash data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets. Other or NA: project construction data. Response 19 – Route mile point: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/procurement, project construction data. Route reference post: crash data. Geographic coordinates: crash data, traffic monitoring data, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, project construction data. Response 20 – Route mile point: Roadway inventory, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data. Other or NA: transportation improvement programs, contracts/procurement, project construction data. Response 21 – Multilevel LRS: Roadway inventory, crash data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, project construction data.

A-30 Geographic coordinates: traffic monitoring data, Travel modeling data, environmental impact and compliance data. Other or NA: contracts/procurement. Response 22 – Route mile point: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/ procurement, project construction data. Link node: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data. Route street reference: Roadway inventory. Multilevel LRS: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, bridge work history data. Geographic coordinates: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inven- tory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/ procurement, project construction data. Response 23 – Route mile point: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs. Link node: Travel modeling data. Route street reference: Roadway inventory, HPMS. Multilevel LRS: Roadway inventory, traffic monitoring data, HPMS, transportation improvement programs. Geographic coordinates: Roadway inventory, crash data, traffic monitoring data, Travel model- ing data, HPMS, pavement inventory and condition data, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs. Response 24 – Route mile point: environmental impact and compliance data, project construction data. Link–node: Travel modeling data. Route street reference: crash data, traffic monitoring data, Inventory and condition data for other assets. Multilevel LRS: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs, contracts/procurement, project construction data. Geographic coordinates: crash data, bridge inventory and condition data, Inventory and condition data for other assets. Other or NA: pavement work history data, bridge work history data, environmental impact and compliance data, contracts/procurement, project construction data. Response 25 – Route mile point: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, contracts/procurement, project construction data. Route reference post: Roadway inventory, traffic monitoring data, Inventory and condition data for other assets. Link node: Roadway inventory, traffic monitoring data, Travel modeling data, HPMS, Inventory and condition data for other assets. Route street reference: Roadway inventory, traffic monitoring data, Inventory and condition data for other assets. Multilevel LRS: Roadway inventory, crash data, traffic monitoring data, HPMS, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, project construction data.

A-31 Geographic coordinates: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environ- mental impact and compliance data, contracts/procurement, project construction data. Response 26 – Route mile point: Roadway inventory, crash data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, contracts/procurement, project construction data. Route reference post: Roadway inventory, crash data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, contracts/procurement, project construction data. Link node: Roadway inventory, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets. Geographic coordinates: Roadway inventory, crash data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, contracts/procurement, project construction data. Other or NA: traffic monitoring data, Travel modeling data, transportation improvement programs, environmental impact and compliance data. Response 27 – Route mile point: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improve- ment programs, environmental impact and compliance data, contracts/procurement, project construc- tion data. Route reference post: crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets. Link node: HPMS, pavement inventory and condition data, bridge work history data. Multilevel LRS: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs. Geographic coordinates: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data. Response 28 – Route reference post: Roadway inventory, crash data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data. Link node: Roadway inventory, HPMS, pavement inventory and condition data, pavement work history data, Inventory and condition data for other assets. Route street reference: Roadway inventory, HPMS, pavement inventory and condition data, pave- ment work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets. Multilevel LRS: Roadway inventory. Geographic coordinates: Roadway inventory, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inven- tory and condition data for other assets, transportation improvement programs, environmental impact and compliance data. Response 29 – Route mile point: Roadway inventory, crash data, HPMS, pavement inventory and condition data, Inventory and condition data for other assets, transportation improvement programs. Route reference post: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data. Link node: traffic monitoring data, Travel modeling data. Geographic coordinates: Roadway inventory, crash data, HPMS, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data. Other or NA: bridge work history data.

A-32 Response 30 – Route mile point: Roadway inventory, crash data, traffic monitoring data, HPMS, bridge inventory and condition data. Route reference post: Roadway inventory, crash data, traffic monitoring data, pavement inventory and condition data, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data. Geographic coordinates: bridge inventory and condition data. Response 31 – Route mile point: crash data, traffic monitoring data, pavement inventory and con- dition data, pavement work history data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/procurement, project construc- tion data. Route reference post: Roadway inventory, traffic monitoring data, HPMS, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transporta- tion improvement programs. Route street reference: crash data, traffic monitoring data, Inventory and condition data for other assets, project construction data. Multilevel LRS: crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, project con- struction data. Geographic coordinates: HPMS, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data. Response 32 – Route mile point: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and con- dition data for other assets, transportation improvement programs, contracts/procurement, project construction data. Route street reference: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, contracts/procurement, project construc- tion data. Multilevel LRS: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inven- tory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, contracts/procurement, project construction data. Geographic coordinates: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, contracts/procurement, project construc- tion data. Responses of Local Agencies Response 1 – Geographic coordinates: crash data, traffic monitoring data, bridge inventory and condition data, Inventory and condition data for other assets. Other or NA: Road inventory, Travel modeling data, pavement inventory and condition data, trans- portation improvement programs. Response 2 – Link node: Roadway inventory, traffic monitoring data, Travel modeling data. Geographic coordinates: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, Inventory and condition data for other assets. Other or NA: transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data. Response 3 – Geographic coordinates: Travel modeling data, pavement inventory and condition data, transportation improvement programs. Response 4 – Geographic coordinates: traffic monitoring data, Travel modeling data, transportation improvement programs. Other or NA: Roadway inventory, crash data, HPMS, pavement inventory and condition data, pave- ment work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/procure- ment, project construction data.

A-33 Response 5 – Route mile point: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS. Response 6 – Route mile point: Roadway inventory, transportation improvement programs. Other or NA: crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inven- tory and condition data for other assets, environmental impact and compliance data, contracts/ procurement, project construction data. Response 7 – Route mile point: Roadway inventory, crash data, traffic monitoring data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs. Link node: Travel modeling data, transportation improvement programs. Geographic coordinates: crash data, transportation improvement programs. Other or NA: HPMS, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/procurement, project construction data. Response 8 – Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condi- tion data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data. 6) If you answered “other” to Question 5, please describe this location referencing method: Responses of DOTs Response 1: “Historic work against bridges is being recorded by project delivery against the actual asset not a location. We derive locations through this association back to the asset but it also simplifies the linkage between projects and the assets they affect.” Response 2: “project coordinate systems are used—modified state plane” Response 3: “contracts/procurement = Districts/Counties, construction = Roadway acceptance data in mileposts. Station numbers (feet) with offsets.” Response 4: “County-Route-Postmile (postmile is not the same as odometer).” Response 5: “Key number for contracts and construction.” Response 6: “Ground Survey Stationing” Response 7: “Work histories, plans, environmental, contracts, and project construction each have their own referencing systems as their primary reference (like a bridge ID). These things have references to assets in the asset databases.” Response 8: “Not available at this time.” Response 9: “bridge Work History is linked to bridge inventory” Responses of Local Agencies Response 1: “Several of the datasets listed above have road-segment-based location referencing.” Response 2: “Most of these data sets are not owned/maintained by our agency and are therefore not applicable.” Response 3: “The majority are NA. As an MPO, we don’t maintain the physical asset data.” Response 4: “bridge Inventory and bridge Work History: unique ID in addition to route/mile point. Signals (‘other assets’) based on route/mile point of ‘primary’ contributing link.”

A-34 7) How does your agency share data with outside users (public and private entities)? Data Set Online (open access) Online (pre- authorized access) Upon request (e.g., data sent via e-mail or a file sharing service) Not shared outside agency Other Roadway inventory (e.g., location, classification, geometrics) Crash data Traffic monitoring data (e.g., speed, volume) Travel modeling data (e.g., household surveys, origin- destination) Highway Performance Monitoring System (HPMS) Pavement inventory and condition data Pavement work history data Bridge inventory and condition data Bridge work history data Inventory and condition data for other assets (e.g., traffic signs, signals, drainage assets) Transportation improvement programs data Environmental impact and compliance data Contracts/procurement data (e.g., bid tabs) Project construction data (e.g., cost/payments, schedule, material acceptance testing, as-built plans) Financial data (e.g., current and historical revenues, expenditures, budgets) Responses of DOTs Response 1 – Upon request: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, trans- portation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Response 2 – Online (open access): HPMS Upon request: Roadway inventory Response 3 – Online (open access): Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data,

A-35 bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, Response 4 – Online (open access): traffic monitoring transportation improvement programs, environmental impact and compliance data. Upon request: Roadway inventory, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, contracts/procurement, project con- struction data, financial data. Not shared outside agency: crash data Response 5 – Online (open access): Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, transportation improvement programs, environmental impact and compliance data. Online (pre-authorized access): crash data, transportation improvement programs, environmental impact and compliance data, project construction data, financial data. Upon request: roadway inventory, crash data, traffic monitoring data, travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and con- dition data, bridge work history data, inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Response 6 – Online (open access): crash data, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs project construction data. Upon request: Roadway inventory, traffic monitoring data, HPMS, financial data. Not shared outside agency: environmental impact and compliance data, contracts/procurement. Other or NA: Travel modeling data. Response 7 – Online (open access): Roadway inventory, crash data, contracts/procurement, project construction data, financial data. Online (pre-authorized access): Roadway inventory, crash data. Upon request: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS. Response 8 – Online (open access): Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improve- ment programs, environmental impact and compliance data, project construction data, financial data. Not shared outside agency: bridge work history data, contracts/procurement. Response 9 – Online (open access): transportation improvement programs, contracts/procurement. Online (pre-authorized access): Roadway inventory, crash data, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Upon request: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and con- dition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Other or NA: traffic monitoring data. Response 10 – Online (open access): Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, environmental impact and compliance data, financial data. Online (pre-authorized access): environmental impact and compliance data, contracts/procurement. Upon request: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, Inventory and condition data for other assets, environmental impact and compliance data. Not shared outside agency: project construction data. Other or NA: Travel modeling data, bridge work history data, contracts/procurement. Response 11 – Online (open access): traffic monitoring data, HPMS. Online (pre-authorized access): transportation improvement programs.

A-36 Upon request: Roadway inventory, Travel modeling data. Not shared outside agency: crash data, traffic monitoring data, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/ procurement, project construction data, financial data. Other or NA: Roadway inventory. Response 12 – Online (pre-authorized access): Roadway inventory, HPMS. Upon request: Roadway inventory, HPMS. Response 13 – Online (open access): Roadway inventory, crash data, traffic monitoring data, pave- ment inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, contracts/procurement, financial data. Upon request: Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs. Not shared outside agency: project construction data. Other or NA: Roadway inventory, Travel modeling data, pavement work history data, bridge work history data, environmental impact and compliance data. Response 14 – Online (open access): Roadway inventory, traffic monitoring data, HPMS, bridge inventory and condition data, transportation improvement programs, contracts/procurement, project construction data. Upon request: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, transportation improvement programs, contracts/procurement, project construction data. Not shared outside agency: crash data, Travel modeling data, bridge work history data, environ- mental impact and compliance data. Other or NA: bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, financial data Response 15 – Online (open access): Roadway inventory, crash data Upon request: Travel modeling data Response 16 – Online (open access): Roadway inventory, traffic monitoring data, HPMS, bridge inventory and condition data. Online (pre-authorized access): Roadway inventory, crash data, bridge inventory and condition data. Upon request: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Other or NA: Inventory and condition data for other assets. Response 17 – Online (open access): Roadway inventory, traffic monitoring data, pavement inventory and condition data, bridge inventory and condition data, transportation improvement programs. Upon request: Roadway inventory, crash data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data. Not shared outside agency: bridge work history data, financial data. Response 18 – Online (open access): Roadway inventory, traffic monitoring data, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, transportation improvement programs, contracts/procurement. Online (pre-authorized access): crash data, bridge inventory and condition data, bridge work history data, contracts/procurement, project construction data, financial data. Not shared outside agency: Travel modeling data, HPMS, Inventory and condition data for other assets, environmental impact and compliance data. Response 19 – Online (open access): Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and con dition data, bridge work history data, transportation improvement programs, contracts/procurement, project construction data.

A-37 Upon request: Roadway inventory, Travel modeling data, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, envi- ronmental impact and compliance data. Not shared outside agency: Inventory and condition data for other assets, financial data. Other or NA: Roadway inventory, traffic monitoring data, HPMS, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, environmen- tal impact and compliance data. Response 20 – Online (open access): crash data, traffic monitoring data, transportation improvement programs, contracts/procurement. Upon request: pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, environmental impact and compliance data, project construction data. Not shared outside agency: Travel modeling data, HPMS, Inventory and condition data for other assets, financial data. Response 21 – Online (open access): HPMS, transportation improvement programs. Online (pre-authorized access): Roadway inventory, crash data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, project construction data. Upon request: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and con- dition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Response 22 – Online (open access): Roadway inventory, crash data, traffic monitoring data, pave- ment inventory and condition data, pavement work history data, bridge inventory and condition data, transportation improvement programs. Upon request: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and con- dition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Response 23 – Online (open access): traffic monitoring data. Upon request: Roadway inventory, Travel modeling data, HPMS, transportation improvement programs. Response 24 – Online (open access): Roadway inventory, traffic monitoring data, Inventory and condition data for other assets, transportation improvement programs. Upon request: HPMS, pavement inventory and condition data, bridge inventory and condition data, bridge work history data, environmental impact and compliance data, contracts/procurement, financial data. Not shared outside agency: Travel modeling data, pavement work history data, project construction data. Other or NA: crash data. Response 25 – Online (open access): Roadway inventory, crash data, traffic monitoring data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, contracts/procurement, project construction data. Upon request: Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs. Other or NA: Travel modeling data, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Response 26 – Online (open access): Roadway inventory. Online (pre-authorized access): Roadway inventory, crash data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work his- tory data, Inventory and condition data for other assets, contracts/procurement, project construction data, financial data.

A-38 Upon request: Roadway inventory, crash data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, contracts/procurement, project construction data, financial data. Other or NA: traffic monitoring data, Travel modeling data, transportation improvement programs, environmental impact and compliance data. Response 27 – Online (open access): traffic monitoring data, transportation improvement programs, contracts/procurement. Online (pre-authorized access): Roadway inventory, traffic monitoring data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, financial data. Upon request: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Response 28 – Upon request: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transpor- tation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Response 29 – Online (open access): Roadway inventory, traffic monitoring data, pavement work history data, bridge inventory and condition data, bridge work history data, transportation improve- ment programs, financial data. Online (pre-authorized access): crash data, environmental impact and compliance data, contracts/ procurement, project construction data, financial data. Upon request: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, pavement inventory and condition data, Inventory and condition data for other assets, contracts/ procurement. Not shared outside agency: HPMS. Response 30 – Online (open access): Roadway inventory, traffic monitoring data, bridge inventory and condition data, transportation improvement programs. Upon request: Roadway inventory, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Other or NA: crash data. Response 31 – Online (open access): Roadway inventory, traffic monitoring data, transportation improvement programs, environmental impact and compliance data, contracts/procurement. Online (pre-authorized access): traffic monitoring data, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data. Upon request: crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, project construction data, financial data. Response 32 – Online (open access): Roadway inventory, traffic monitoring data, bridge inven- tory and condition data, Inventory and condition data for other assets, transportation improvement programs, contracts/procurement. Upon request: Roadway inventory, crash data, traffic monitoring data, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/ procurement, project construction data, financial data. Not shared outside agency: Travel modeling data, HPMS, pavement work history data, bridge work history data. Responses of Local Agencies Response 1 – Upon request: Roadway inventory, crash data, traffic monitoring data, pavement inventory and condition data, bridge inventory and condition data, Inventory and condition data for other assets, financial data.

A-39 Not shared outside agency: Travel modeling data, transportation improvement programs. Other or NA: HPMS, pavement work history data, bridge work history data, environmental impact and compliance data, contracts/procurement, project construction data. Response 2 – Online (open access): Roadway inventory, traffic monitoring data. Online (pre-authorized access): crash data, Travel modeling data, HPMS, transportation improve- ment programs. Response 3 – Upon request: Travel modeling data, pavement inventory and condition data, trans- portation improvement programs, contracts/procurement, financial data. Response 4 – Online (open access): transportation improvement programs. Upon request: traffic monitoring data, Travel modeling data, financial data. Not shared outside agency: contracts/procurement. Other or NA: Roadway inventory, crash data, HPMS, pavement inventory and condition data, pave- ment work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, project construction data, financial data. Response 5 – Not shared outside agency: Roadway inventory, crash data, traffic monitoring data, Travel modeling data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Response 6 – Online (open access): Roadway inventory, transportation improvement programs. Upon request: Travel modeling data. Other or NA: crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, environmental impact and compliance data, contracts/procurement, project construction data, financial data. Response 7 – Online (open access): crash data, traffic monitoring data, Travel modeling data, Inventory and condition data for other assets, transportation improvement programs, environmental impact and compliance data, financial data. Other or NA: Roadway inventory, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, contracts/procurement, project construction data, Response. Response 8 – Online (open access): Roadway inventory, crash data, traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, transportation improvement programs, financial data. Upon request: Travel modeling data, environmental impact and compliance data, contracts/ procurement. Response 9 – Online (open access): Roadway inventory, transportation improvement programs, environmental impact and compliance data. Upon request: Travel modeling data. Other or NA: traffic monitoring data, HPMS, pavement inventory and condition data, pavement work history data, bridge inventory and condition data, bridge work history data, Inventory and condition data for other assets, contracts/procurement, project construction data, financial data. 8) If you answered “other” to Question 7, please describe this data sharing method: Responses of DOTs Response 1: “The majority of most frequently requested data has been moved to our public portal for viewing. All of the data on this site can be downloaded for the public’s use at the links on this site to our open data portal.” Response 2: “real time roadside message boards.” Response 3: “contracts/procurement = Although some information is confidential per Federal Law, most contract information is available online, or by request if not available online. Procurement information is exempt from public records law until after selection meetings. Once the final selection meeting has been held, information can be made available to the public.” Response 4: “Public Records Act request.”

A-40 Response 5: “crash data owner is the Maryland State Police which is associated to a milepost or intersection/ This is shared on the State Open Data Portal. SHA analyzes and edits the data to its true location via mile point. this analyzed data is not shared to the public and is highly sensitive even within the agency. SHA has an internal system to display and share data called Enterprise GIS. All data in the Other column is shared via eGIS internally. project and contract info is shared on the SHA website in the project Life Cycle sharepoint pages in tabular form; there are some maps but not all projects make it on this page. It is not comprehensive. pavement, bridge and asset inventory is currently in progress for a GIS centric public accessible dashboard. It has not been approved for release but is ready for release.” Response 6: “crash data is ‘owned’ by the State Police.” Response 7: “Don’t know would have been a useful additional category.” Response 8: “Not available at this time.” Response 9: “crash data is shared in a limited capacity (certain details only) and then upon request.” Responses of Local Agencies Response 1: “Most of these data sets are not owned/maintained by our agency and are therefore not shared.” Response 2: “Other or N/A: we are not the owners of these datasets.” Response 3: “As an MPO we often serve as a clearinghouse for data. The data that is not ours, identified as Other here, we prefer to first direct them to the original data collection agency or provide data available and identify the source for direct contact for additional details.” 9) What strategies would improve (or have improved) data sharing and access within your agency? If other strategies are applicable, please specify them in the entry boxes titled “Enter another option.” Strategy Major Effect Minor Factor No Effect Not Applicable Improved metadata Increased use of web-based data storage and access Improved database management systems Reduced use of hardware and software that require specialized data format *Enter another option* *Enter another option* Responses of DOTs Response 1 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Response 2 – Major Effect: Improved metadata, Increased use of web-based data storage and access. Minor Factor: Improved database management systems. No Effect: Reduced use of hard- ware and software that require specialized data format. Response 3 – Major Effect: Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Minor Factor: Improved metadata. Response 4 – Minor Factor: Improved metadata, Improved database management systems. No Effect: Increased use of web-based data storage and access, Reduced use of hardware and software that require specialized data format. Response 5 – Major Effect: Improved metadata, Improved database management systems, Reduced use of hardware and software that require specialized data format. Minor Factor: Increased use of web-based data storage and access. Response 6 – Major Effect: Increased use of web-based data storage and access, Improved database management systems, Improved framework to centralize and present data. Minor Factor: Improved metadata, Reduced use of hardware and software that require specialized data format. Response 7 – Major Effect: Increased use of web-based data storage and access, Improved database management systems. Response 8 – Major Effect: Increased use of web-based data storage and access, Reduced use of hardware and software that require specialized data format. Minor Factor: Improved metadata. Not Applicable: Improved database management systems

A-41 Response 9 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require special- ized data format. Response 10 – Major Effect: Improved metadata, SharePoint. Minor Factor: Increased use of web- based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Response 11 – Major Effect: Increased use of web-based data storage and access, Improved database management systems, Governance. Minor Factor: Improved metadata, Reduced use of hardware and software that require specialized data format. Response 12 – Major Effect: Increased use of web-based data storage and access. Minor Factor: Improved metadata. Response 13 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Response 14 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Response 15 – Major Effect: Improved metadata, Reduced use of hardware and software that require specialized data format. Not Applicable: Increased use of web-based data storage and access, Improved database management systems. Response 16 – Major Effect: Improved database management systems, Reduced use of hardware and software that require specialized data format. Minor Factor: Improved metadata. Not Applicable: Increased use of web-based data storage and access. Response 17 – Major Effect: Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Minor Factor: Improved metadata. Response 18 – Major Effect: Use of Enterprise-Level Business Intelligence Vendor Products, Civil Integrated Management Imitative, Development of an Enterprise Data Warehouse (based on and designed for current and planned business processes and needs, and developed in collaboration with program areas). Minor Factor: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Response 19 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Senior management champion. Response 20 – Major Effect: Improved database management systems. Minor Factor: Improved metadata, Reduced use of hardware and software that require specialized data format. No Effect: Increased use of web-based data storage and access. Response 21 – Major Effect: Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Minor Factor: Improved metadata. Response 22 – Major Effect: Increased use of web-based data storage and access, Improved database management systems, Web-GIS Interactive Mapping of Enterprise Data. Minor Factor: Improved metadata, Reduced use of hardware and software that require specialized data format. Response 23 – Major Effect: Increased use of web-based data storage and access, Improved database management systems. Minor Factor: Improved metadata. No Effect: Reduced use of hardware and software that require specialized data format. Response 24 – Major Effect: Improved metadata, Increased use of web-based data storage and access. Minor Factor: Improved database management systems, Reduced use of hardware and software that require specialized data format. Response 25 – Major Effect: Increased use of web-based data storage and access, Improved database management systems. Minor Factor: Improved metadata, Reduced use of hardware and software that require specialized data format. Response 26 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems. Minor Factor: Reduced use of hardware and software that require specialized data format. Response 27 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Data registry. Minor Factor: Reduced use of hard- ware and software that require specialized data format.

A-42 Response 28 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Response 29 – Major Effect: Improved metadata, Improved database management systems, Reduced use of hardware and software that require specialized data format. Response 30 – Major Effect: Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format, Data governance, standards and requirements for sharing/availability. No Effect: Improved metadata. Response 31 – Major Effect: Reduced use of hardware and software that require specialized data format. Minor Factor: Improved metadata, Increased use of web-based data storage and access, Improved database management systems. Response 32 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Responses of Local Agencies Response 1 – Major Effect: Increased use of web-based data storage and access. Minor Factor: Improved metadata, Improved database management systems. No Effect: Reduced use of hardware and software that require specialized data format. Response 2 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems. Minor Factor: Reduced use of hardware and software that require specialized data format. Response 3 – Minor Factor: Improved metadata, Improved database management systems. No Effect: Increased use of web-based data storage and access, Reduced use of hardware and software that require specialized data format. Response 4 – Major Effect: Reduced use of hardware and software that require specialized data format. Minor Factor: Improved metadata, Increased use of web-based data storage and access, Improved database management systems. Response 5 – Not Applicable: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Response 6 – Minor Factor: Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. No Effect: Improved metadata. Response 7 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require specialized data format. Response 8 – Major Effect: Improved database management systems, Reduced use of hardware and software that require specialized data format. Minor Factor: Improved metadata, Increased use of web-based data storage and Response 9 – Major Effect: Improved metadata, Increased use of web-based data storage and access, Improved database management systems, Reduced use of hardware and software that require special- ized data format. 10) What data management tools are most useful for accessing and sharing data within your agency? Responses of DOTs Response 1 – “SQL Server, ETL tools to regularly create packaged datasets, ArcGIS Online.” Response 2 – “We currently use an access front end to access our warehoused data. This has proved challenging for our casual users. We are moving to a web based portal for internal users that presents reports/maps/dashboards and SQL connected excel worksheets for users to filter and work with enterprise data.”

A-43 Response 3 – “file servers, Sharepoint Intranet.” Response 4 – “ESRI Open Data, ArcServer, GeoServer, Custom Oracle Application.” Response 5 – “The most useful tool has been a system that integrates all the different referencing systems.” Response 6 – “Microsoft Office (Excel); Access; MySQL; IBI Managed Reporting Environment; SSRS; Crystal Reports; SharePoint.” Response 7 – “Document Retrieval System, Data Libraries (GIS and non-GIS), Enterprise databases.” Response 8 – “We are in the process of implementing ArcGIS for Server and ArcGIS Online as part of a multi-user/editor and transparent environment. Other than that, communication is the biggest key factor on having a successful enterprise data system for us.” Response 9 – “GIS, Data Warehouse, Web tools, starting to use BI/Visualization, specialty software.” Response 10 – “KanPlan (Kansas GIS portal), Data Warehouse Reports Portal.” Response 11 – “We are still researching this.” Response 12 – “REST services are becoming a standard.” Response 13 – “SAP Business Objects Suite, Oracle Business Intelligence Suite, Data Connections in Microsoft Access and Excel.” Response 14 – “eGIS Portal.” Response 15 – “Using the same database platform.” Response 16 – “Data Warehouses, Web-GIS interface for Viewing Data.” Response 17 – “Online repositories are the most useful tools for sharing data.” Response 18 – “Web based GiS mapping and data location creation and maintenance tools.” Response 19 – “SSRS, SharePoint with BI tools.” Response 20 – “LRS, Geospatial and mapping tools: a) ArcGIS Online, aka UPlan b) Spatial appli- cations d) Roadway digital imaging c) roadlog tied to mapping and roadway digital imaging.” Response 21 – “GIS, EXCEL.” Response 22 – “Special Apps, TOAD, MS Access, Oracle, SQL server.” Response 23 – “ArcGIS, ArcGIS Online, Oracle, SQL, various file sharing methods.” Responses of Local Agencies Response 1 – “Not sure.” Response 2 – “Relational databases, GIS, statistical software, internal data library (“Data Depot”), external data library (Data Hub).” Response 3 – “In the process of learning some.” Response 4 – “Shapefiles and excel. Not everyone is the agency is familiar with RDBMS or ever MS Access so excel becomes the best choice followed by ArcGIS.” 11) Does your agency have mechanisms in place for incorporating feedback from data users in your agency into the data collection process? M Yes (please describe or provide examples in the box below) M No Responses of DOTs M Yes: 15 responses Response 1 – Yes: “Not as an agency practice, but there are some instances where users can directly provide feedback.” Response 2 – Yes: “Somewhat, but definitely could be improved.” Response 3 – Yes: “Web forms and e-mail.”

A-44 Response 4 – Yes: “Multiple methods based on application—Web—Helpline—Internal e-mail.” Response 5 – Yes: “E-mail comments options, steering committees, surveys.” Response 6 – Yes: “Currently, we communicate ideas, methods and issues with each other, but not a formal process in place yet.” Response 7 – Yes: “We take suggestions and incorporate them to guide future improvements.” Response 8 – Yes: “Users can request that data items and subject areas be mapped from specific systems to reporting warehouses and business intelligence suites. Users can request that data value pick lists be maintained (e.g., add, retire, or modify usage).” Response 9 – Yes: “traffic Counts.” Response 10 – Yes: “We encourage users of data to report errors and since it’s quick/easy (and we make changes immediately), users freely supply feedback.” Response 11 – Yes: “Only through notification to the data owners at the users’ initiative.” Response 12 – Yes: “Very informal, formative stage as we develop new LRS and data integration.” Response 13 – Yes: “Collaborate with pavement management and HPMS on data collection priorities.” Response 14 – Yes: “mail or Call - the content contact is on most web pages.” Response 15 – Yes: “occasional surveys, but mostly ad hoc meetings/discussions as needed.” M No: 15 responses Responses of Local Agencies Response 1 – Yes: “Through meetings and comments delivered on suggestion boxes.” M No: 7 data Warehousing 12) What is the estimated amount of data that your agency maintains [expressed in data storage units, such as terabytes (1012 bytes)]? If no reliable estimate is available, please enter “unknown.” Responses of DOTs Response 1 – Roadway inventory; Oracle current 6992 MB, historical 6413 MB, DB2 0.28 gigabyte. Response 2 – “50 terabytes.” Response 3 – “At least 1/2 TB.” Response 4 – “0.5 terabytes; but really unknown.” Response 5 – “2 TB.” Response 6 – “Several terabytes as a min.” Unknown – 25 respondents Responses of Local Agencies Response 1 – “Approx. 20 terabytes.” Unknown – 8 responses 13) Approximately what percentage of your agency’s transportation-related data is currently stored and managed using commercial cloud computing services? Cloud Computing: Date are stored and managed on remote computers “in the cloud.” These computers are owned and operated by others and connect to users’ computers via the Internet. More than 50% 21–50% 11–20% 1–10% None Unknown

A-45 Responses of DOTs M More than 50% – None M 21–50% – 2 responses M 11–20% – 1 response M 1–10% – 22 responses M None – 3 responses M Unknown – 3 responses Responses of Local Agencies M More than 50% – None M 21–50% – None M 11–20% – None M 1–10% – 3 responses M None – 5 responses M Unknown – 1 response 14) In the next five years, what percentage of your agency’s transportation-related data is anticipated to be stored and managed using commercial cloud computing services? More than 50 21–50% 11–20% 1–10% None Unknown Responses of DOTs M More than 50% – 4 responses M 21–50% – 5 responses M 11–20% – 5 responses M 1–10% – 3 responses M None – None M Unknown – 14 responses Responses of Local Agencies M More than 50% – 1 response M 21–50% – None M 11–20% – None M 1–10% – 2 responses M None – 2 responses M Unknown – 4 responses The survey is complete. Thank you for your participation!

Next: Appendix B - Survey Respondents »
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TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 508: Data Management and Governance Practices develops a collection of transportation agency data management practices and experiences. The report demonstrates how agencies currently access, manage, use, and share data.

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