There are multiple challenges for improving the sharing and use of private sector shared mobility data, including: 

  • Coordinating data collection and analysis across systems and modes – The combination of the Mobility Data Specification 1 and the General Bike Feed Specification 2 provide excellent standards for the exchange of micromobility data, and their use continues to grow. However, similar standards do not currently exist for taxi fleets, TNCs, microtransit, or car sharing. Currently, each jurisdiction sets its own rules, and either the public agency or the private provider determines the format for providing the requested or required data.
  • Data quality​ – Better methods are needed to ensure that mobility providers collect and provide accurate data. There are needs for audits to verify that the data match with ground truth. There is also a necessity to develop uniform algorithms to calculate certain performance metrics when there is a lack of uniformity in either the definition, assumptions, formulas, or data translations associated with producing these metrics. The Mobility Data Collaborative’s Data Sharing Glossary and Metrics for Shared Micromobility is one effort to address data quality issues. 3
  • Tradeoffs between the legitimate needs of public agencies and the protection of private and proprietary data – This is the largest and most complex challenge. On one hand, pre-aggregated data from mobility providers may not meet an agency’s data needs in operations or enforcement. On the other hand, mobility providers are concerned about protecting their proprietary information from competitors, understanding how the data will be used, and protecting the privacy of their users. The concern over privacy is shared by other groups with an interest in protecting citizen privacy: 
    • Trip level data, whether or not provided in real-time, is particularly problematic. Numerous studies have shown that detailed location data can often be combined with other data sources to re-identify individuals associated with the trip. 
    • Data breaches where hackers obtain access is also an issue. At the same time, pre-aggregated datasets that do not address a specific use case may be of no value in meeting the legitimate, transportation management needs of public agencies. 
    • Freedom of information and similar laws are a major problem. Most of these laws have exemptions for PII but do not recognize location data as PII. In localities where Uber is required to provide trip-level data as a condition of operating in the locality, such data are almost immediately the subject of a FOIA request. 4
  • Public sector understanding, skills, and resources to effectively manage large, sensitive datasets – Most public sector agencies lack the skills, expertise, and speed required in understanding and managing these data.

Referencing Page:


  • 1Open Mobility Foundation. (n.d.). Mobility Data Specification. Retrieved June 4, 2020, from GitHub:
  • 2NABSA. (n.d.). GBFS & Open Data. Retrieved June 4, 2020, from North American Bike Share Association:
  • 3Mobility Data Collaborative. (2020). Data Sharing Glossary and Metrics for Shared Micromobility. SAE.
  • 4Sivaram, S.-p. T. (2020, June 24). Director of Policy, Cities, and Transportaton at Uber and Global Head of Privacy and Security Policy at Uber. (K. P. Michael McGurrin, Interviewer).