Data Sharing Guidance for Public Transit Agencies—Now and in the Future (2020)

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CHAPTER 7 Conclusions and Next Steps The research summarized in this report identified the critical factors that drive data sharing decisions and defined several models for data sharing by transit agencies, considering both sharing of transit agency data and access to external data by transit agencies. There were several key findings that represent common themes and critical issues and challenges observed across transit agencies and even across sectors. This chapter summarizes the important takeaways from this research. In addition, this is an evolving field. Mobility data is changing, as is the legal context and the conversation around data privacy and ownership. This chapter describes how transit agency data sharing may evolve in the future. Finally, this research identified several gaps where additional research is required. These are summarized in Section 7.3. 7.1  Key Findings Based on the interviews and literature and information review, the following are the key findings about data sharing for transit agencies. Transit Agencies Share Data Frequently and See Many Benefits • Transit agencies collect data on the transit system, including route, schedule, and vehicle location data, which are commonly shared and contributes to customer information. Sharing these data types can promote transparency and generate insightful research. Addition- ally, route, schedule, and vehicle location data are frequently shared by transit agencies (10 of 11 transit agency interviewees stated that their agencies share this data publicly). Private devel- opers routinely use route, schedule, and vehicle location data in customer-facing apps that help transit passengers plan their routes and find out when transit vehicles will arrive at stops and stations. Some transit agency interviewees reported receiving data from these travel planning apps. • Transit agencies collect a wide variety of data on transit passengers. Sharing this data also generates value, including from research that can improve system performance and increased advertising revenue for the transit agency. Transit agencies collect data on passengers, including fare and bank card transaction data, Wi-Fi and Bluetooth data, video data, and passenger count data, all of which shows how the transit agency’s network is being used. This data is often of interest to customers, journalists, real estate developers, and researchers. Sharing data can promote transparency and generate insights and innovation that are beneficial to the transit agency. It may even generate revenue, particularly through advertising. However, these data types have the potential to be used to identify individuals. Transit agencies need data privacy protocols to determine which data sets should be shared and what measures (aggregation, censoring, adding noise) should be taken to protect privacy. 54 

Conclusions and Next Steps   55   • Transit agencies share some data openly and share other data sets directly with partner institutions or individuals through private data sharing agreements. The most common type of open data, according to the transit agency interviewees, was route, schedule, and vehicle location data, but transit agencies also share ridership, on-time performance, survey data, and financial data publicly on their websites. In addition, all transit agency interviewees indicated their agencies respond to public records requests for data. Several transit agencies have established data sharing relationships with research institutions and reported beneficial insights gained through these relationships. • Information disclosure laws govern many aspects of data sharing by transit agencies. Infor- mation disclosure laws, which require public agencies to share information requested through a public records request, vary by state (most transit agencies are not subject to the federal FOIA). Transit agencies should ensure they understand the legislation in their state, includ- ing data exemptions and whether processing fees can be charged. If transit agencies find that data that poses privacy risks is not exempted from public records requests, they may consider working with state legislators to change legislation. Ensuring these exemptions are in place can also help transit agencies access external data sets. Transit Agencies May Be Able to Increase the Value of Data Sharing in the Future with the Development of New Data Standards, Moving Toward Open Data and Tools, and Leveraging the Interests of the Private Sector • Data standards have the potential to increase the value of public transit data sharing and make transit agency use of external data sets more efficient. The majority of transit agency interviewees were supportive of the idea of standards for public transit data types, noting that standards could promote the development of shared tools and other resources. Transit agencies are looking to external organizations for standards creation and adoption. • Open software tools could augment the value of public transit data and help transit agencies use external data sets. A general movement toward open data and open tools can benefit transit agencies. • Private company interviewees in the MaaS industry, including private mobility providers and user information app developers, are interested in transit data. Some expressed a willingness to further discuss the potential to purchase data from transit agencies; others questioned the notion of monetizing data collected by public transit agencies. They are especially interested in geospatial details of transit stations as well as data, such as passenger counts, that can help them plan their services. Data Sharing Challenges are Part of Broader Data Management Needs • Often, transit agency data collection processes are byproducts of other functions of the transit agency (e.g., fare collection, operations, management). More deliberate data collection efforts can ensure transit agencies maximize the value of their data. • Collecting, cleaning, processing, documenting, and cataloging data requires significant effort. Several transit agency interviewees noted the significant technical needs and effort required to prepare data for sharing. Those transit agencies that had developed procedures for processing and cataloging data found that this saved time responding both to public and to internal data requests. Transit agencies may consider charging processing fees for public records requests that require significant effort (if allowed under state law). • Transit agency interviewees identified internal organizational and technical needs to improve their processes for sharing data. The majority of transit agency interviewees 

56   Data Sharing Guidance for Public Transit Agencies—Now and in the Future indicated their agencies do not have a centralized data repository, or a staff or group dedicated to data management. These interviewees noted that establishing dedicated staff could help make data management a priority. In addition, they expressed frustration that data is stored across divisions, making it difficult to find, use, and share. Data-focused staff can drive transit agencies’ data sharing programs, developing goals, identifying needs, creating internal data management processes, including a data catalog, and evaluating data sharing opportunities. Transit Agencies are Beginning to Harness the Value of External Data, but Challenges Remain • There is potential value in linking transit agency data sets to external data sets. External data sets can help transit agencies understand first- and last-mile trips and modal alternatives to transit. Parking and curb-use information can also be of use to transit agencies. • Transit agencies access external data sets, either by purchasing data or leveraging a mobility services partnership. Or in some cases, they may gain access to data through a third party. The transit agency interviewees acknowledged the challenges of negotiating data sharing agreements with private mobility providers, even when they have a service agreement. Despite these challenges, transit agencies see value in these data sources, and at least two of the transit agencies have negotiated access to data from TNCs. • Although private sector data, app, and mobility company interviewees expressed interest in cooperating with transit agencies, they also cite privacy concerns as one reason their com- panies avoid sharing individual-level data with transit agencies. There are no transportation sector-specific privacy laws at the federal level that govern transit data sharing. In some states, transit agencies may need to work with state legislatures to ensure that data on individuals is exempted from state information disclosure legislation. Or transit agencies can work to access information through a third party. • Cities are beginning to exercise their regulatory power by demanding private mobility pro- viders submit mobility metric data when applying for operational rights on city rights of way. These requirements provide examples for public transit agencies establishing partnerships with private companies. In addition, transit agencies can work with cities to ensure that data requirements meet transit agency needs and that data is shared between the two public entities. 7.2  Future of Data Sharing for Transit Agencies There are several factors that may change over time. First, transportation technology and data are evolving. Second, legislation around data management and data privacy may evolve. Third, there is a trend toward open data and open data tools. Evolving Technology As sensing and fare payment technology evolves, transit agencies will collect new and different data. In addition, new mobility options and MaaS platforms generate additional data. As transit agencies develop their internal data management staff and resources, it is important to build in flexibility to accommodate new data types and uses. Evolving Regulations States are increasingly regulating data collection, storage, and dissemination by public agen- cies. As data breaches and security of personal information become more of a concern, states may move to impose additional restrictions and disclosure requirements. States, such as California, have taken a leading role in enacting privacy data laws, and other states will likely 

Conclusions and Next Steps   57   follow. Thomas (2017) hypothesized that a decision that impacts the way transit agencies manage data sets, including individual trips, may eventually be handed down by the U.S. Supreme Court. In the European Union, the GDPR, approved in 2016 and enforced beginning in 2018, defines a comprehensive set of regulations around privacy. It requires that consent and terms be clear, trans- parent, and written in easily understood language. It specifies that individuals own their data and must be informed if their data is being transferred to another party or if there had been a data breach. Data-as-a-Service companies that operate in Europe maintain that the owners of the raw data generated from smart devices are individual device users. These private companies leverage the usage of data to derive analytical data products and insights at various spatial-temporal levels. The technology companies claim ownership of the data derivatives generated from their algorithms, not the original data. As described in Section 5.3, there has also been movement to update public records legislation to remove barriers to the sharing of private sector data with public sector agencies. These chal- lenges are not limited to the transit sector and are likely endemic to the nascent nature of privacy protection laws. In the utility industry, some regulators have placed privacy restrictions on a third party’s ability to share the customer’s data with a partner provider. Although these restrictions are intended to protect consumers, some state regulators are reviewing and revising their rules to allow secondary release when it comes to enabling consumer convenience and guaranteeing customers reap the intended benefits of sharing data. Changes to public records legislation could help transit agencies access more external data. Protecting data from public records requests could also enable transit agencies to monetize data or leverage it in data-for-data trades. However, the viability of these options will depend on how public perception and expectations of data ownership and data privacy evolve. Open Data and Open Data Tools There appears to be a general trend toward open data and open data tools. The success of GTFS is much touted in the public transit sphere, and there is a push for additional open data standards. Initiatives such as SharedStreets and the MDS seek to extend open data practices to private sector mobility data. The World Bank’s Open Transport Partnership (2016) is another innovative data sharing model used mostly for developing countries, but may it be a potential model for developed countries as well. 7.3  Future Work This effort identified several areas for additional study, including the following: • A technical analysis of data privacy that identifies privacy risks by data type and provides methods to add noise or set aggregation and sample size requirements to protect privacy. • Guidance on data cybersecurity for transit agencies to use internally and to share with part- ners who receive sensitive data. • Analysis that quantifies the potential costs of data privacy and security risks. • A 50-state survey of data privacy and information disclosure laws that apply to state and local government entities to provide more details on specific requirements that may be imposed on transit agencies with respect to data sharing. • Collaborative standards-making activities to enable more effective sharing of both transit agency and external data sets and to promote open data and open data tools. • A cross-agency study of the level of effort required for different data management tasks to help transit agencies better evaluate costs of data sharing and internal data analysis.