Data Practices Types of Data Practices
- Date: February 1, 2022
Jump to section
Practices for Obtaining Data
For transit agencies, making good use of data begins with identifying, collecting, and storing the data sources your agency may already have—and in some cases, accessing useful data for planning from external sources. This data may be manually collected or represent digitized paper records, but increasingly agencies rely on passive, sensor-based systems to automatically harvest large quantities of data. With raw data in hand, a best practice is to use common data standards to format and manage data. Doing so paves the way for quicker analyses or allows for broader dissemination of data to customers and stakeholders. Whether publishing data or making use of open sources like the US Census, transit agencies stand to benefit from participating in the broader open data ecosystem.
Manual Data Sources
For some agencies, digitizing existing records or simply collecting more data manually will be the first priority when working with data. Such data includes ridechecks, trip requests, on-board customer surveys, and customer service complaints, as well as internal records on asset condition, safety incident reports, and maintenance data.
Passive Data Sources
Passive, or automatic, data sources collect information using electronic sensors and are capable of generating large volumes of highly granular data. Although these technologies carry a higher capital cost than manual data sources, passive sources have lower marginal costs as well as increased data coverage, availability, and reliability.
Emerging Advances in Data Collection
While sensor-based, passively generated data is increasingly part of the state of the practice for transit agencies, emerging technological advances are changing how such data is generated: from internet-connected parts and systems to customer cellphone location data, to the data generated as agencies provide more customized services.
Existing Data Standards
Standards can be either formal data standards that are adhered to across the industry or informal data practices that are defined at each agency. Regardless, standards are a key determinant of how much agencies—as well as customers and stakeholders—can get out of data. The General Transit Feed Specification (GTFS) for both static transit schedules and real- time updates is the most prevalent standard for data used in the transit industry today.
Emerging Data Standards
Standards are emerging to provide demand response and other flexible transit services with the same level of visibility as GTFS provides to fixed-route services. Systematically recording and managing trip history and ridership data are also set to be improved by emerging standards.
As data producers and data users, transit agencies can benefit from accessing external open datasets as well as opening their transit data. Open data practices lead agencies to promote service awareness and transparency, improve efficiencies, spur innovations, improve customer satisfaction, become more engaged with customers, and improve service and data quality.
Practices for Using Data
Data-driven planning decisions are the key to maximizing the use of limited resources for the greatest benefit of transit riders. While the use of data to inform planning and performance monitoring decisions is not new, the richness of new data sources provides agencies with the ability to conduct more precise evaluations of performance and to plan services with greater clarity. However, many small agencies do not have the resources to collect or analyze all the data they need to. Partnerships with other organizations—whether they be another transit agency, a non-profit, a state agency, a business, or other entity—can help provide insights, technology, or expertise. Data also provides a means to assess who transit serves and how well it serves them in richer detail than ever before.
For transit service planning, data provides key insights for decision-makers when designing and evaluating service changes. Though some data like ridership and revenue hours will be tabulated by the agency itself, external datasets such as population and employment estimates will play a role in many planning decisions. As services change and fleets age, decisions on future year capital investment needs can also be made on the basis of asset data.
As communities grow, travel behaviors change, and agency conditions fluctuate, so too do metrics like ridership, on-time performance, service efficiency, revenues, and costs. Transit performance monitoring is the process of reporting a set of performance measures repeatedly over time. However, rural, tribal, and small urban agencies structure their performance monitoring efforts, new data sources provide new opportunities to gauge performance.
Partnerships Providing Access to Data
Not all data is “open,” and not all open data is readily used. As a result, agencies must rely on other organizations to obtain datasets vital to transportation planning. Both public and private sector entities can be potential partners, including local school districts, colleges and universities, major employers, metropolitan planning organizations (MPOs), regional planning agencies (RPAs), municipal departments, state DOTs, and other transit agencies.
Partnerships for Data Analysis and Technology
ITS devices and thorough data analysis come at the cost of both capital outlays and staff expertise. Transit agencies need not conduct all procurement or data analysis themselves: often, there are partners that can help agencies procure, develop, or maintain technology or who can process datasets that new technologies produce. In some cases, agencies are sharing their own proprietary technology with other agency partners.
Using Data to Build Partnerships
It can be difficult for transit agencies to prove their importance to the agencies and organizations that fund, oversee, or partner with them. When building a new relationship with a partner organization, providing proof of the effectiveness of an agency can be even more difficult. Certain types of data analyses can help illustrate a transit agency’s importance to a community and make the case for more funding support from current and existing partners.
Using Data for Access and Equity
Evaluating accessibility to key destinations and jobs is an emerging trend in the industry. Transit agencies have begun to pay more attention to accessibility metrics, which examine how well transit provides connections to key destinations.
Although equity analysis is required through Title VI, there are opportunities for agencies to address these questions more thoroughly. Equity considerations include service offered, fare payment types, trip purpose analysis, and trip planning accessibility.