Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies (2011) / Chapter Skim
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Pages 19-49
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P A R T 2 Use of Information Technology Tools and Data Management Practices to Support Data Sharing and Integration in Transportation Agencies
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The primer covers risk management approaches for data programs and also discusses how data is used to support risk management programs within a transportation agency in general. This primer addresses IT issues and challenges that impact data sharing and integration, and therefore decision making, especially for PBRA decisions.
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Many state transportation agencies use various types of location referencing methods in their road network linear referencing systems. Some of the methods may include routemilepoint, distance from origin, and latitude/longitude locations.
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Provides for a comprehensive road network to support agency geodatabase. Data providers for local road networks not required to use/follow same data collection standards and definitions as state transportation agencies.
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Clearly documented definitions and standards applied to each of these data quality components helps to ensure that the highest quality data is available for decision-making. Need to identify which business units in the agency are responsible for determining each of these components of data quality.
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B High 22 Data sharing standards of all stakeholders may not be co mp atible with your agency standards. Providing a copy of your agency data catalog or data definitions and standards can help address this issue.
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I High 31 Need to develop shared datasets and business terminology definitions between data program managers and all departments/business units, including IT office. Standard business terminology dictionary supports development of applications and data systems that are transferable across all business units and transferable to external users of the application systems.
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when establishing data sharing agreements. B Low Governance 34 Differences of opinions may exist between IT offices and business units regarding the roles and responsibilities for defining data definitions, standards, and policies for the use of data and information.
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Requires close coordination from both the IT office and business units to participate in development of the business terminology dictionary. I Medium Maturity Models 38 Need to use maturity models to assess overall progress of agency's data governance evolution, which ultimately impacts the agency's ability to share and integrate data and information systems with other internal or external data sources.
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Knowledge management (KM) systems KM systems can be used to Provide easy and quick access to data, information, reports in a variety of formats to support business needs; Provide automated versioning control for documents; Serve as repository of information on lessons learned; Contain contact information for data stewards, data business owners for specific data systems; provide links to data dictionaries, data catalogs; and Provide information on data governance policies and procedures.
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The database model is being designed with the flexibility to integrate data from additional road networks, as needed. When the geodatabase is implemented, it will be the source of location data for a new Traffic Data System and Crash Data System, as well as support existing department business programs.
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Solution One of the most effective methods identified for addressing the existence of silos is the development of enterprise databases. The implementation of an enterprise database usually relies on participation from the business units and IT offices.
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Michigan DOT has a structured data management program that includes data policies and standards, and data dictionaries for the many applications systems that are used to support business operations. In order to provide the highest quality data and information, a concerted effort is made to evaluate what data are (and will be)
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The business units, however, may focus their risk management efforts on the potential failure of infrastructure assets, such as bridges or pavements in a state DOT. Each of these types of risks is important and should be addressed as part of an agency's risk management program.
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This includes GIS tools used for display of maps and the use of business intelligence tools, such as dashboards and scorecards, and KM systems for storing and sharing data and information. For the purpose of identifying a unique proposed solution, the following discussion explains how GPS, GIS, and wireless technology are used as part of a study involving sharing and exchange of data to support electronic freight management.
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7. Drayage operator then proceeds to railroad terminal #2 to deliver the container(s)
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The level of granularity or precision level that is needed for data collection programs may vary across business units within a state transportation agency. For instance, although a 1-mile increment unit may be sufficient for road inventory data collection programs, pavement management programs may require 1/10-mile segments to be used for data collection in order to meet federal or other reporting requirements.
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Integrating real-time data requires coordination between the state DOT IT office, the internal users of the real-time data, and the transportation management centers that collect the data. Data sharing agreements, which include detailed system requirements for data collection, storage, QA/QC, and processing, are needed to ensure that the data is available to supplement traditional traffic data collection programs.
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These may be business data owners and data stewards for particular systems such as road inventory, traffic, pavement, bridge, and asset management systems. Providing training opportunities to staff in the use of new technology and tools also encourages their support of letting go of "doing things the way they've always been done." The work groups are used to identify potential solutions and best approaches for implementing improved business processes.
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These plans also are used to identify data management policies and standards and data governance structures that are used to manage the collection and dissemination of data and information. Data governance also can be used to identify the data stewards, data business owners, and COIs for particular data programs.
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External data products also may require additional internal agency processing before the data is ready for integration into internal database systems. Solution When external sources of data are used to supplement data collection activities for a state transportation agency, the collection requirements should be very detailed and include data definitions, file formats, and any QA/QC procedures that must be applied to the data.
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Solution Develop data sharing agreements between agencies that exchange data and information, to ensure that data is provided within the financial, legal, and technical requirements of each agency. The data sharing agreements should include, at a minimum, the following items: • Costs of data collection and processing, if there is a cost incurred, for delivery of data from one agency or organization to another; • Legal requirements regarding the use of the data; and • Specific technical requirements regarding the integration of the source data into other data environments (i.e., does the data have to be converted into a different format, or does the data require special software to process it within a GIS environment?
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GIS data models can be developed to allow for multiple data layers to be integrated within the GIS. Although each data layer can be linked to a specific jurisdiction (region, county, city)
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In this case, data archiving may be an option to preserve the data for future processing at a time when additional resources are more readily available. Summary -- IT Issues Each of the IT issues that impact data sharing and integration have been discussed in this section.
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The next examples illustrate how risk management programs are used at two state transportation agencies in Washington and Minnesota. 3.1 Washington State Department of Transportation The Washington State Department of Transportation (WSDOT)
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Mn/DOT has been proactive in developing a data business plan, including a framework (Figure 2.3.2) that helps the department to ensure that they continue to maintain the data systems that are needed to meet business needs and assess risks to the agency due to loss of data from any of their core data systems.
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Figure 2.3.2. Mn/DOT data business plan framework.
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TIS is a complex mainframe system that was developed 30 years ago and is used to maintain roadway, traffic volume, and crash data. There were issues and differences of opinion between the business units and the IT office regarding the best approach for replacing TIS.
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This example illustrates how a risk assessment process can be used to evaluate competing investments for all programs, including data programs.11 Source: TIS Risk Assessment Final Report, November 17, 2009. Figure 2.3.3.
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2-A-1 AADT -- Annual Average Daily Traffic ADOT&PF -- Alaska Department of Transportation and Public Facilities ADT -- Average Daily Traffic ATIP -- Annual Transportation Improvement Program ATP -- Area Transportation Partnership AVL -- Automatic Vehicle Location BI -- Business Intelligence Caltrans -- California Department of Transportation CAPTA -- Costing Asset Protection: An All Hazards Guide for Transportation Agencies CCTV -- Closed Circuit Television CDOT -- Colorado Department of Transportation CEVP -- Cost Estimate and Validation Process COI -- Community of Interest COPACES -- Computerized Pavement Condition Evaluation System CRA -- Cost Risk Assessment C-TIP -- Cross-Town Improvement Project DRG -- Dynamic Route Guidance EIR -- Environmental Impact Report FARS -- Fatality Analysis Reporting System FTE -- Full-Time Equivalent FTP -- File Transfer Protocol GDOT -- Georgia Department of Transportation GIS -- Geographic Information System GPS -- Global Positioning System HAS -- Highway Analysis System HPMS -- Highway Performance Monitoring System IMEX -- Intermodal Move Exchange IT -- Information Technology ITS -- Intelligent Transportation System KM -- Knowledge Management KPI -- Key Performance Indicators Mn/DOT -- Minnesota Department of Transportation MPO -- Metropolitan Planning Organization MTC -- Metropolitan Transportation Commission NBI -- National Bridge Inventory OPM -- Office of Organizational Performance Management PACES -- Pavement Condition Evaluation System A P P E N D I X A Acronyms, Abbreviations, and Initialisms
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PBRA -- Performance-Based Resource Allocation PC -- Personal Computer Pga -- Peak Ground Acceleration QA/QC -- Quality Assurance/Quality Control QOL -- Quality of Life ROI -- Return on Investment RTTM -- Real-Time Traffic Monitoring SFR -- Statewide Freight Resiliency TAU -- Traffic Analysis Unit TIS -- Transportation Information System T-MDID -- Truck-Mounted Driver Interface Device TxDOT -- Texas Department of Transportation UPACS -- User Profile and Access Control System VDOT -- Virginia Department of Transportation WDU -- Wireless Drayage Updating WSDOT -- Washington State Department of Transportation XML -- Extensible Markup Language 2-A-2
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