Practices on Acquiring Proprietary Data for Transportation Applications (2019)

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5 This chapter provides background information, specifies the scope of the study, outlines the research approach, details the survey and interview processes, and describes the organization of the report. Background Data are a critical input into the effective planning, design, operation, and maintenance of transportation infrastructure. Agencies routinely collect various data items to support their planning, design, operation, and maintenance functions. The 2005 Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users mandated the establishment of a real-time system management information program to monitor travel conditions on major highways throughout the United States. The goal was to improve transportation system security, address congestion problems, improve incident management, and facilitate the distribution of highway travel information at the national and regional levels. The mandate was established to set up in all states a system of basic real-time information to manage and operate highways; identify longer-range real-time highway and transit monitoring needs and prepare plans to address those needs; and establish the capability and means to share data with state and local governments, as well as the public. As part of this requirement, state and local governments were asked to develop or update regional intelligent transportation system (ITS) architectures. At the same time, technological advancements have led to new types of transportation data that can provide insights into a wide range of travel characteristics. For example, GPS-based vehicular location data generated by commercial fleets and passenger automobiles with in-vehicle navigation systems have been aggregated by third-party data providers into various products, such as speed and O-D. The rapid growth of smartphone use has enabled a number of crowdsourced applications. All major online maps now offer real-time information on roadway traffic conditions, color- coded according to level of congestion. For example, Google Traffic uses a large number of GPS-enabled mobile phones to generate and display speed estimates on a relative scale from slow to fast. Waze developed a smartphone app that allows users to report crashes, hazards, congestion, and other incidents as they travel along the highway. These data items contain rich information on uses and conditions of the transportation system for motorized as well as non-motorized modes. They often provide greater temporal and wider geographical coverage than traditional data sets. State DOTs and MPOs have recognized the potential of these data. Many have begun exploring the use of these data sets for their transportation applications. Real-time travel-time and incident information have C H A P T E R 1 Introduction

6 Practices on Acquiring Proprietary Data for Transportation Applications been integrated into the advanced traveler information system (ATIS), a component in the ITS architecture. Archived vehicular and non-motorized trip data have been used by agencies to produce performance measures, support model enhancement, and aid with other transporta- tion planning and programming applications. However, agencies face a number of challenges associated with obtaining and using such data. First, data providers often consider their original sources and their methodologies to clean, process, and aggregate the data as proprietary. As a result, it is difficult for transportation agencies to directly evaluate data sources and determine if the samples are reasonably represen- tative of the traveling public or freight carriers. The lack of transparency is often cited as the main reason agencies are hesitant to acquire the data. Second, the licensing agreements often place restrictions on what data may be shared. This might create a potential conflict, given that agencies are typically obligated to comply with federal, state, and local open records laws. Third, these data often come in large quantities, posing challenges to agencies’ legacy data-management systems. Additional investment in IT infrastructure to upgrade computing, storage, and management capabilities would be needed. Further, the effort of integrating these data with existing agency data systems is often dependent on staff possessing the requisite skills. Objectives of the Study The primary objectives of this study are to compile and review practices that state DOTs and MPOs have leveraged to acquire and use these emerging forms of proprietary transportation data. This study focused on practices pertaining to: • The types of data that have been acquired and their uses; • Agency experience on data use, such as integration, evaluation, and caveats; • The procurement process, including decisions to acquire data, RFP development, product and vendor evaluations, contract negotiations, and use agreements; and • How agencies handle legal and privacy concerns. Current procurement practices, as well as advice from responding agencies, are summarized in this report. Study Approach The information presented in this synthesis was collected through a review of literature on current practices related to proprietary data, a formal survey of state DOTs and large MPOs, and follow-up interviews with several state DOTs and MPOs—five of which are profiled in depth in Chapter 4. A comprehensive literature review of current and past efforts at the federal, state, and MPO level to acquire and use proprietary data was conducted to establish what types of data agencies have obtained and their uses. Numerous resources—including the Transportation Research International Database, the University of Kentucky libraries, and web searches—were used to identify literature. Findings of the literature review assisted with the development of survey questions and facilitated discussions through much of the synthesis report. The study team designed and administered a survey on the state of the practice for proprietary data acquisition. The survey sought information on three major aspects of proprietary data: (1) data items acquired and applications, (2) procurement method, and (3) use experience. The initial survey was reviewed by the panel of this synthesis project and pre-tested at panel

Introduction 7 members’ agencies in February 2018. The survey was refined based on the panel’s comments and suggestions. The final survey was distributed to state DOTs via an email distribution list with the assistance of the AASHTO Data Management and Analytics Committee on March 1, 2018. For states that are not on this distribution list, the study team identified DOT personnel in the area of data management, planning, or operations through an online directory search. All 50 state DOTs were invited to participate in the survey. The survey was also distributed to 22 large MPOs with populations of more than 2.5 million with the assistance of the Association of Metropolitan Planning Organizations. A response was requested by March 22, 2018. Email reminders were sent to invitees who had not responded to the survey. The deadline was postponed for agencies that were unable to complete the survey on time. During the period, the study team sent follow-up emails and made phone calls to increase the response rate. Appendix A contains a copy of the survey questionnaire. Forty-two state DOTs and three MPOs responded to the survey or participated in phone interviews between March and June 2018. Responses are summarized in Table 1. The state response rate was 84%, satisfying the minimum threshold requirement set out by NCHRP. Of those states that responded, 79% indicated that they have acquired at least one proprietary data set. Figure 1 shows states that have acquired proprietary data, that have not acquired any proprietary data, and that did not respond to the survey. Survey Status Number of States Percentage of States Invited 50 100 Responded 42 84 Have acquired proprietary data 33 79 of states that responded Have not acquired proprietary data 9 21 of states that responded Table 1. Summary of state responses. No survey responseResponded with “Yes” Responded with “No” Figure 1. State responses to the question, “Have you acquired proprietary data?”

8 Practices on Acquiring Proprietary Data for Transportation Applications State DOT staff from Ohio, Wisconsin, Arizona, and Kentucky were interviewed, as were staff from the Atlanta Regional Commission, an MPO responsible for transportation planning in a 10-county area of North-Central Georgia. Their agencies’ experiences procuring and using proprietary data are discussed in Chapter 4. The case examples supplement the high-level survey findings reviewed in Chapter 3. Agencies thinking about obtaining proprietary data from third-party vendors can leverage information from the case examples to streamline the data acquisition process. Report Organization This synthesis report consists of five chapters: • Chapter 1: Introduction. This chapter provides background information and summarizes the purpose and study approach of the project. • Chapter 2: Overview of Proprietary Data. Results of the literature review are summarized in this chapter. An overview of proprietary data types and their sample uses is provided, including speed or travel time, O-D, freight, incident, and non-motorized travel. In addition, current procurement practices and legal issues associated with proprietary data are also discussed. • Chapter 3: Practices on Proprietary Data Acquisition. This chapter summarizes and discusses the main findings based on the responses received from state DOTs and MPOs. • Chapter 4: Case Examples. This chapter documents proprietary data acquisition in greater detail by looking at the practices and experience of four state DOTs and one MPO. Reflec- tions by agency staff interviewed about the experience gained in the process are presented in the form of peer advice. • Chapter 5: Conclusions. This chapter summarizes key observations and findings assembled through the literature reviews, survey, and interviews. It contains a list of successful prac- tices as reported by respondents and interviewees for peer agencies to consider when pro- curing data.