Open Data: Challenges and Opportunities for Transit Agencies (2015)

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In the past 5 years, more and more transit agencies have begun making schedule and real- time operational data available to the public. “Open data” provide opportunities for agencies to inform the public in a variety of ways about transit agency services. The purpose of this synthesis is to document the current state of the practice and policies in the use of open data for improved transit planning, service quality, and customer infor- mation; the implications of open data and open documentation policies; and the impact of open data on transit agencies and the public and private sectors. The synthesis focuses on successful practices in open transit data policies, use, protocols, and licensing. A literature review and survey collected key information about open transit data. The survey was sent to 67 transit agencies around the world and had a 100% response rate. Of the 67 sur- veys received, three were from Canadian agencies and 14 from European agencies. U.S. responses represent agencies that carry a total of more than 5.4 billion passengers annually (annual unlinked trips), with U.S. agencies’ annual ridership ranging from 1.8 million (a county transit system in Florida) to 2.6 billion (Metropolitan Transportation Authority in New York City). The background of open transit data in the United States is as follows. Prior to 1998, data generated by technologies deployed by public transit agencies were not made available to the public. In 1998, Bay Area Rapid Transit released schedule data in the comma-separated values (.csv) format; this was the first known release of transit data to the public. Tri-County Metropolitan Transportation District of Oregon (TriMet) worked with Google in the cre- ation of General Transit Feed Specification (GTFS, originally developed by Google and containing static schedule information for transit agencies, including stop location, route geometrics, and stop times) in 2005. Massachusetts Bay Transportation Authority (MBTA) opened the agency’s data in 2009. As of April 2014, according to City-Go-Round, almost 29% of U.S. transit agencies provided open data. In 2003, the Digital Agenda for Europe, Public Service Information Directive was issued, requiring all European Union member states to release public sector information, including open public transport data. Many pub- lic transit agencies in the Asia-Pacific region are beginning to open their data as well, such as a recent initiative to combine and release the data from many public transit operators in Tokyo, Japan. In addition, not only have public transit authorities benefited from providing open data, but the public, private, and independent sectors also have realized benefits. Transit authorities that have embraced transparency by providing open data have improved the perception and increased the visibility of transit. They also have been able to use the data they are releasing to the public to make internal improvements. The public now has access to many free appli- cations that provide real-time and static transit information, which greatly facilitates travel using transit. Private businesses have been created or expanded to work with open transit data and have developed innovative applications that, in some cases, could not have been devel- oped in a public agency. Finally, the independent sector, consisting of academic institutions and research and development organizations, has been instrumental in researching, analyz- ing, using, and promoting the creation and use of open transit data. SUMMARY OPEN DATA: CHALLENGES AND OPPORTUNITIES FOR TRANSIT AGENCIES

2 This synthesis examines and documents the state of the practice in open transit data using the following five elements: • Characteristics of open transit data: – Reasons for choosing to provide open data – Standards and protocols for providing open data – Underlying technology used to generate the open data • Legal and licensing issues and practices: – Legal and licensing issues – Public disclosure practices • Uses of open data: – Applications – Decision-support tools – Visualizations • Costs and benefits of providing open data • Opportunities and challenges: – Techniques to engage users and reusers of data – Challenges associated with providing open data – Impacts on transit agencies and the public and private sectors. SUMMARY OF PROJECT FINDINGS Key statistics from the study follow. • Fifty-seven or almost 83% of the survey respondents provided open data. • The top four reasons for not providing open data, according to the survey, were – Too much effort to produce the data/we do not have the time or people to do the work required; – Too much effort to clean the data; – We cannot control what someone will do with our data; and – We do not know the accuracy of our data. In addition to the four case examples conducted as part of this synthesis project and pre- sented in chapter seven, two examples show the value and power of open transit data: • Moscow’s transit authority relied on open data to determine whether more investment in rail networks was necessary or if other services could better meet demand. Instead of building a new rail line at considerable expense, the authority restructured bus service, which allowed flexibility for future shifts in population. Not only did the authority avoid incurring more than $1 billion in infrastructure costs, but the restructured bus service also saved an average of 3 minutes per trip during the morning commute, amounting to 10 hours of travel time for each rider every year. • In New Jersey, NJ Transit released data on passenger flows to the public in 2012. Third parties quickly analyzed ridership at different times of day and were able to pinpoint underutilized rail stops, which led to more express trains and a savings of 6 minutes in the average commuting time during peak hours. In summary, based on the literature review, the responses to the questionnaire, and the case examples, the key findings of this synthesis project are as follows: • The benefits to the agency strongly support open transit data. The availability of open transit data encourages innovation that could not be accomplished solely by agency staff. The top five overall benefits experienced by survey respondents were (1) increased awareness of our services; (2) empowered our customers; (3) encouraged innovation

3 outside of the agency; (4) improved the perception of our agency (e.g., openness/trans- parency); and (5) provided opportunities for private businesses. • Engaging application developers, other data users, and customers is an approach that can accomplish several critical tasks, including: – Obtaining feedback on data anomalies and data quality issues; – Ensuring that some portion of the applications developed by third parties meets the needs of customers; and – Finding out more about how people want to use/reuse the data. There are several ways to engage developers and customers. Results of the survey indi- cated that the most effective methods are conducting face-to-face events, conferences, and “meetups.” Meetups are informal meetings to discuss particular topics, such as application development. • The results of the literature review and survey indicate that standards and commonly used formats can be used to facilitate the generation and use of open data. Further, using standards makes it easier to transfer applications from one agency to another. • Open transit data result in innovation that could not be accomplished within a transit agency. That is not to say that sufficient intellect does not exist in a transit agency; rather, it is an issue of having sufficient resources to develop applications and conduct analyses at the scale that can be done in an open market. Specific findings based on the five elements include: • Characteristics of open transit data: – The top three types of open data are routes, schedules, and station/stop locations; – The most prevalent underlying technologies that produce open data are sched- uling software, geographic information system (GIS) software, computer-aided dispatch (CAD)/automatic vehicle location (AVL), and real-time arrival prediction software; – The overwhelming reasons for opening transit data are related to customer infor- mation—increasing access to this information and improving the information and customer service; – The primary factor that went into the decision about what data to open was the ease of releasing the data (more than half of the survey respondents indicated this); – A variety of standards and formats are being used, including GTFS (47 or 83.9% of respondents), Extensible Markup Language (XML) (26 or 46.4%), and .csv (18 or 32.1%), followed by GTFS-realtime (15 or 26.8%); and – Degree of openness n Thirty-two or 57.4% of the respondents reported that the data are completely open (everyone has access); n Forty-seven or 83.6% reported that the data are available in formats that are easily retrieved and processed; n Forty-nine or 87.3% reported that there is no cost for their open data; and n Forty-three or 79.2% reported that there are unlimited rights to use, reuse, and redistribute their data. • Legal and licensing issues and practices: – Twenty-nine or 50.9% of the survey respondents reported that they require a license or agreement to use their agency’s open data; – The top three elements that license agreements cover are the right to use the agency’s data; nonguarantee of data availability, accuracy, or timeliness; and liability limita- tions for missing or incorrect data; – Only one respondent experienced any legal issues resulting from the release of open data to the public; and

4 – The top three steps that respondents took to disclose their data publicly were convert- ing transit data into formats suitable for public use; improving data quality to ensure accuracy and reliability; and adopting an open, nonproprietary data standard. • Uses of open data: – The top five types of customer applications that have been developed as a result of providing open data are (in descending order of frequency) trip planning, mobile applications, real-time transit information (arrival/departure times, delays, detours), maps, and data visualization; – The top five decision-support tools that have been developed are data visualization, service planning and evaluation, route layout and design, performance analysis, and travel time and capacity analysis; – Almost two-thirds (33 or 63.5%) of respondents do not track usage of their open data; – The two most prevalent methods of tracking are to monitor data downloads and keep track of applications developed; – For mobile applications, an equal number of respondents reported Android and iOS applications; and – Sixteen respondents reported a total of almost 266 million Application Programming Interface (API) calls per month. • Costs and benefits of providing open data: – The top five types of costs associated with providing open data are staff time to update, fix, and maintain data as needed; internal staff time to convert data to an open format; staff time needed to validate and monitor the data for accuracy; staff time to liaise with data users and developers; and web service for hosting data; – Almost 90% (43 or 89.4%) of respondents could not quantify how much time is spent on any of these activities; – There was limited information regarding the actual labor required from specific staff in the organization and the costs associated with open data; and – The top three benefits experienced by survey respondents are increased awareness of their services, empowerment of their customers, and encouragement of innovation outside of the agency. • Opportunities and challenges: – Almost 70% (33 or 69.6%) of respondents engage or have a dialogue with existing and potential data users and reusers; – Twenty-five or 75.8% of respondents engage data users and reusers to obtain feed- back on data anomalies and data quality issues. Twenty-four or 60% of the respon- dents use face-to-face events to engage these groups; – The organizational impacts on the agency resulting from opening the data ranged from increased transparency to better and more accurate internal data to lower costs to provide information. The majority of negative impacts were related to resources required to maintain an open data program; – Impacts on the customer were numerous, including better and more accessible infor- mation for customers; better perception, visibility and awareness of services, and improved customer satisfaction; – In terms of impacts on the public, creating and improving access to additional and higher quality public services was mentioned, along with improving public perception/image of transit, making transit more competitive, providing better regional coordination of services, encouraging innovation, and providing a better transit experience; – The impacts on the private sector are primarily providing business/commercial and development opportunities, including new and expanded companies (e.g., creating a new ecosystem of private entrepreneurs); enabling innovation and the creation of applications that may not have been created by the public sector; and adding value to existing public services; and – Challenges were noted by survey respondents in five areas: (1) resources and orga- nizational issues; (2) data quality and timeliness issues; (3) standards and formatting

5 issues; (4) marketing issues relating to making the open data known and addressing branding issues; and (5) technical issues. Several conclusions can be drawn from the results of the synthesis project, including: • The benefits to the agency strongly support open transit data; • The impacts of open transit data on customers and the general public are significant; • The impacts on the private sector have been encouraging over the past several years. Applications and visualizations that could not necessarily have been conceived or developed by a transit agency have been created; • The legal fears often thought to be barriers to opening transit data have not been realized; • Standards greatly facilitate the use of open transit data, although this sometimes requires additional effort in producing the data; • Engaging with data users and reusers has the potential to increase the value of the appli- cations and visualizations; • Five factors lead to a successful open data program: (1) obtaining and maintaining management-level support for such a program; (2) recognizing the need for the appropri- ate level of resources required to provide and maintain open data; (3) establishing ways to monitor data accuracy, timeliness, reliability, quality, usage, and maintenance; (4) creating and maintaining licensing or registration; and (5) having an ongoing dialogue with both developers and customers, a practice shown to increase the value of the data and products that are based on the data.