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Data Sharing Principles for Mobility and Delivery

In our increasingly connected world, more data than ever is captured and shared each day. Knowing how to share that data can be difficult.

That is why Flex worked with urban and economic development consulting company HR&A Advisors in 2022 to develop a series of best practices for sharing data.​

This set of principles will help protect users’ personal data, and improve the working relationship between sharing and requesting parties.


Common Data Sharing Use Cases

Most data requests fall within four use cases. Distinguishing characteristics of each use case are influenced by agency mandate, legal authority, and level of government.

Law Enforcement

Vehicle-related accidents and/or person-related incidents.

Licensing / Regulation

Licensing and permitting requirements and/or trip-related compliance.


Urban and transit planning, including congestion, curb, and emissions management and accessibility.

Event Management

Traffic and curb management within a specific, geo-fenced area.

Benefits & Risks of Data Sharing

It can help protect rider safety, assist planning to reduce vehicle emissions, or increase accessibility for people with disabilities. The Washington, DC, Department of Transportation used mobility data in 2017 to identify pick-up/drop-off (PUDO) locations with disruptive night-time traffic. After a dedicated PUDO zone pilot showed reductions in congestion and unsafe behavior, DC expanded the program to more than 30 locations.

The primary risk is violating individuals’ privacy, which can result in financial, moral, and physical harm. In 2014 researchers obtained and de-anonymized data on 173 million New York City taxi trips, identifying trips taken by celebrities and revealing their residences and habits. Shared data can also harm firms by providing competitors with sensitive business information.

Best Practices for Data Sharers

While data requests from government entities will continue to increase, companies should advocate for consistent approaches and outcomes to help inform mobility and delivery data sharing so it is effective for all parties.

While each mobility and delivery data company has unique data collecting requirements and sharing processes that it should follow, these best practices can help companies create an industry-wide approach to ensure positive public and private outcomes.

You can refer requesters to the best practices on page 3 of this guide to help them understand how they can increase benefits and reduce risks from data sharing. Use past successful experiences to guide new requesters towards more effective approaches.

You should ask requesters for highly specific goals. Highly specific data requests can help you identify and provide the right set of data for a narrow purpose rather than having to over-share broad, potentially sensitive information. This helps you work in partnership with requesters to solve policy problems and makes the process more efficient for both parties.

Given the nascency of delivery data sharing, you should proactively and collaboratively shape the narrative in this space. This could include defining some use cases that do not depend on sensitive data or establishing narrow pilots that address common questions. Adopting an industry-wide approach can help sharer concerns and public privacy remain at the forefront of the discussion.

Best Practices for Data Requesters

How data requesters approach collecting and sharing data can determine the level of benefit and risk they generate. Using these 4 best practices can help maximize benefits and collaborate with data sharers.

You should have a clear reason for the type and granularity (e.g., level of geographic accuracy) you request. This helps sharers better understand the purpose of your ask and allows them to respond to your needs.

You should replicate effective data sharing agreements, formats, and processes from other jurisdictions and to streamline data collection and minimize operational burdens on requesters and sharers.

You should not ask for data as it is generated in real time and for “breadcrumb” data (end-to-end trip location data). Sharing this detailed data presents the highest risks to privacy and is the most technically burdensome to manage.

You should ask for and/or store data that is scrubbed or aggregated to exclude personal data that is identifiable or re-identifiable. You should exempt personal data from public records requests.