Data Interoperability Enables Mobility as a Service

Guest author Jackson Crane is an RMI alum.

Download the report, Collaborating Toward Data Interoperability for Mobility Transformation here.

Imagine a scenario in which people can travel via a wide variety of mobility options that seamlessly get them where they want, when they want, how they want, at a lower cost—to both them and the environment—than driving. These mobility options include a combination of high-efficiency public transit, microtransit, bikeshare, carshare, and ridehail. We call this “mobility as a service” (MaaS), and we believe it is fundamental to the future of transportation.

This future requires a robust and easily accessible transportation-data backbone. Enormous stockpiles of transportation data are created and used by public transit agencies, private transit providers, and commuters. Currently, however, this data is largely siloed. Our goal is to facilitate improved standardization, availability, and quality of multimodal transit data, in order to shift toward MaaS. The data that enables that shift is called interoperable transit data.

In our newly released white paper, Collaborating Toward Data Interoperability for Mobility Transformation, RMI presents the current barriers to data interoperability, a set of best practices for data publication, near-term solutions to overcome some barriers, and a framework to tackle entrenched industry obstacles.


Qualitatively, it is understood among transportation service providers (TSPs) that improving transportation information and discoverability is beneficial for ridership for both public and private transportation. Data interoperability can be thought of in terms of tiered opportunities, where the tiers are: 1) static information; 2) real-time information; 3) predictive information; and 4) integrated booking and payment.

Based on research results, we estimate that the total opportunity from all tiers of data represents a potential 5 to 10 percent boost in ridership across public transportation, ridehail, bikeshare, and carshare. This boost in ridership has the potential to increase personal mobility on alternative modes by up to 9 billion personal miles traveled (PMT) across the U.S. This represents a $3 billion to $6 billion opportunity.

As MaaS gains more market share over privately owned vehicles, the business opportunity for improved transit data is expected to rise commensurately. Furthermore, the generation and publication of this data has impact beyond user discoverability and integrated booking and payment. As higher-quality data is incorporated into public and private transit systems, the operations and offerings of the TSPs, as well as of municipal systems, can be optimized through rider behavior and usage analytics.


1. Quality and incomplete data—Often the quality of data published by TSPs is poor or incomplete. For example, real-time location data is often inaccurate, published infrequently, or is missing for certain services. In other cases, certain transit authorities or TSPs do not publish data elements critical for users to make informed transit choices, such as vehicle location, fare data, or park-and-ride information.

2. Data standardization—Well-utilized data standards for certain modes don’t exist, such as ridehail and carshare, and for other modes, such as fixed-route transit, the data standards are incomplete. Nonexistent standards and a lack of industry consensus prevent the simple and scaled adoption of TSPs into user-facing applications. Incomplete standards prevent certain organizations from publishing all data that they may internally collect that provides value to users.

3. Technology and design—Certain technological or design barriers exist that prevent complete functionality. For example, integrated booking and payment processing technology, although it already exists, is not accessible and simple to adopt for all authorities and TSPs.

4. Incentives—In some cases, transportation providers and/or their technology vendors face a disincentive to make interoperable transportation data available. For example, some transportation network companies (TNCs) disallow real-time information about pickup times and costs to be shown alongside that of competitors, limiting a robust marketplace facilitated by innovative apps.

5. Public engagement—Often, tools and capabilities exist to bring transit information to users, but current or potential users do not know how to use them, or even that they exist.


Several near-term opportunities exist for public and private transit service providers to improve transit data interoperability and capture additional ridership—at an attractive return on investment (ROI)—that don’t involve multistakeholder efforts. The solutions in RMI’s report have been shown to have a quick payback period, and have been successfully implemented by many peer agencies and companies.

Mass transit agencies can publish existing data in well-accepted data formats, such as GTFS and GTFS Realtime. For agencies that have not upgraded equipment so as to produce real-time data, studies show there is a high-ROI opportunity to do so. TSPs without established data standards, such as TNCs, taxis, and carshare, can continue to improve functionality in their respective data-sharing mechanisms (APIs and similar).

Municipalities and larger government institutions have a strong role to play in educating citizens, providing investment for efforts related to data interoperability, and aligning incentives among service providers and application developers. The U.S. Department of Transportation and the Transportation Research Board are already taking strong steps toward overcoming these barriers.


Overcoming many of the barriers described here requires an approach reflecting broad and varied understanding of the space combined with deep technical knowledge, as well as buy-in and ownership from a critical mass of adopters. We think the greatest way to bring this expertise together and to build critical mass to overcome the barriers outlined here is to build a multistakeholder consortium that brings together perspectives and provides resources to develop solutions, without putting the onus of development on one particular party.

There is considerable precedent for similar, successful organizations. A first example is the FIX Trading Community, which established and maintains the FIX trading standard, now the standard used internationally for buy- and sell-side financial services companies. Another successful example is the SUTI transportation data standard. This standard has enjoyed success in Scandinavia as a taxi dispatch mechanism, and is sustained, improved, and disseminated by a not-for-profit governing body.

With a similar structure to these successful organizations, a transit data interoperability consortium can build or adopt successful data standards, gain industry momentum, and maintain those standards in perpetuity. In addition, a multistakeholder group can develop and optimize new technologies and designs that will benefit the entire industry.

In partnership with Trillium Transit, RMI is pursuing a project to bring stakeholders together as a first step toward building such a consortium. Stay tuned for updates on this project, and please contact Greg Rucks ( if your organization is interested in participating.

As the industry adopts more open and interoperable data standards and practices, the potential of mobility as a service is unlocked. As travelers begin to consider “alternative” mobility options before their own car, a new transportation paradigm is unlocked: one that is cheaper, is less stressful, and has a lower carbon footprint.

Download the report here.

To learn more about participating in the consortium, contact Greg Rucks (