Policy

Spin’s Commitment to Responsible Data Sharing and User Privacy

Spin’s Commitment to Responsible Data Sharing and User Privacy

Since its founding, Spin has believed that partnership and trust are key to scaling responsibly, helping cities and universities to innovate and deliver new technology on their terms. This was formalized with Spin’s Partnership Promise in 2018, which established five principles that Spin is committed to in its relationships with cities and universities. Included in the Partnership Promise are two principles related to the sharing and privacy of user data:

  • Proactively share anonymized data with partners
  • Protect user privacy

These principles have become increasingly important with greater adoption of shared micromobility and the subsequent surge in the amount of data — including raw trip data — required by many public agencies. With this increase in data sharing comes a significant risk of reidentifying individual users and their travel patterns, compromising confidential and proprietary business information, and potential liability for data-security breaches of those with whom we share data.

Spin recognizes the value that mobility data can provide for program oversight, policy, and planning purposes. That is why we’ve always committed to sharing data with our partners while ensuring that user privacy is protected. With that in mind, we’ve expanded on these two principles from our Partnership Promise with the following standards intended to achieve a balance of sharing and privacy. Included below are more details on how we hold ourselves to each of these standards and some specific actions we’ve taken to demonstrate how we are following through.

We are committed to proactively sharing anonymized data with partners by:

Delivering data to partners with a demonstrated need while upholding user privacy

  • We are responsive to data-sharing needs in cities and college campuses where we operate, collaborating to establish mutually agreed upon terms to facilitate data sharing, while upholding our commitment to privacy. Spin also partners with mobility data platforms to give public agencies access to vehicle status and trip data in a secure way via heat maps and metrics dashboards, which protects user privacy while also providing our partners with the needed data for compliance, policy, and planning purposes.

Using data to help achieve safe, sustainable, and equitable transportation networks

The above map, created by Spin’s GIS Specialist Julio May, shows the increase in ridership in East Portland following the start before and after the April 6 start of our partnership with PBOT. This data visualization emphasizes the role data can plan in understanding the impact of policy decisions.

Leading the industry in helping to develop mobility data standards and best practices, which includes:

Using data to develop innovative partnerships and research

  • This is exemplified in our partnership with Ford and the Virginia Tech Transportation Institute, where an extensive study was initiated using fixed-camera and on-scooter data collection tools, as well as post-ride survey data, to analyze rider behavior and environmental circumstances, including how they might influence scooter safety on the Virginia Tech campus.

We are committed to protecting user privacy by:

Standing up for user privacy and requesting the same of our partners

  • Spin is an active voice for user privacy and data security, demonstrated by these privacy recommendations from early 2019, which were predictive of subsequent developments in mobility data sharing.
  • This is further exemplified in our contributions to the public forums and organizations leading the work on mobility data, including the OMF, MDC, and NABSA as mentioned above, but also through individual partnerships with cities and college campuses, researchers, and other partners in our work with mobility data.

Believing in data privacy and protection by design

  • Ensuring the privacy and protection of user data is a mandate, not an option, which is recognized across our teams. Our intention is to ensure that data privacy and protection processes are integrated in our products and systems from the beginning, rather than addressed after the fact. That’s why we have cross-functional teams dedicated to privacy and security, from Policy and Legal to Product and Data, to ensure this approach is reflected throughout our business.

Remaining transparent with our operations and giving users control of their data

  • Our Privacy Policy details all data that Spin may collect to enable use of our services, including the categories of data collected, why it’s collected, and what it’s used for, in order to provide users with a comprehensive understanding of their use of our services.
  • Users have a choice to opt in or otherwise limit the data collected, and we provide them the right to know (and delete) the data we collect, giving them access to and control over their own data.

Collecting only the data that is needed and not retaining it for longer than necessary

  • Spin uses the data and information collected to facilitate the use, administration, and operation of the services we provide, as well as to inform riders about other information that may be relevant to their use of our services. While these purposes may adapt or change to best fit our business, we do not collect or retain data unless a specific and relevant purpose is identified.

Establishing Trust Through Data

Sharing anonymized mobility data to inform compliance, policy, and planning use cases, while safeguarding user privacy, requires a thoughtful approach. Our Partnership Promise ensures that we maintain equal focus on both of these principles and that we build trust with both our partners and our riders. But trust must be earned, and actions speak louder than these words.

We hope to continue demonstrating that our approach to data sharing and privacy protection can be balanced for all involved and help establish greater trust across the micromobility industry on the sensitive, yet essential, topic of data.

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