Below are a collection of policy and technical resources related to the handling and protection of MDS and other types of mobility data. They are provided here to aid cities in developing their own policies around data privacy, security, and transparency.
These resources are provided for reference and do not represent an endorsement or official policy statement of the Open Mobility Foundation.
- Privacy Principles, Policies, and Guidelines
- Permit & Licensing Requirements
- Data Sharing
- Data Processing, Aggregation, and Anonymization
- Risk Assessment
- Open Data
- Data Visualization
- Outreach and education
Policy documents related to the privacy implications of mobility data collection, storage, and use.
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Open Mobility Foundation: MDS Privacy Guide for Cities
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Los Angeles, CA: LADOT Data Protection Principles (updated June 2020)
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Portland, OR: PBOT Managing Mobility Data
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San Diego, CA (SANDAG): Privacy Impact Assessment for Micromobility Data
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San Jose, CA: Shared Micro-Mobility Permit Data Protection Principles
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Seattle, WA: SDOT Mobility Data Privacy and Handling Guidelines / Privacy Principles
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Mobility Data Collaborative: Guidelines for Mobility Data Sharing Governance and Contracting
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Mobility Data Collaborative / Future of Privacy Forum: Mobility Data Sharing Assessment Toolkit
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Vianova: Presentation to POLIS network about GDPR & MDS (see pg. 19-28)
- Vianova: MDS GDPR statement, which provides information on how GDPR applies to MDS data and how the parties involved can be compliant.
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EU Joint Research Center: Guidelines for public administrations on location privacy
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Minneapolis, MN: Proposed Privacy Principles
- Shared-Use Mobility Center: Objective-Driven Data Sharing for Transit Agencies in Mobility Partnerships
- Washington, DC: Confidential and Non-disclosure Agreement for sharing data with academic instituions.
For a complete list of cities using MDS, see the Mobility Data Specification readme
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Austin, TX: Director Rules for Deployment and Operation of Shared Small Vehicle Mobility Systems
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Long Beach, CA: Shared Micro-Mobility Program
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Los Angeles, CA: 2020 Dockless Mobility Six-Month Permit Extension
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Louisville, KY: Dockless Vehicle Policy
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San Francisco, CA: Powered Scooter Share Program Permit
Methodologies and tools for ingesting, aggregating, and anonymizing mobility data.
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Minneapolis, MN: Mobility Data Methodology and Analysis
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Portland, OR: Managing Mobility Data
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SAE Mobility Data Collaborative: Data Sharing Glossary and Metrics for Shared Micromobility and Data Sharing Glossary and Metrics for Shared Micromobility, availble here. Must provide email address to download.
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European Commission: Article 29 WP Opinion on Anonymisation Techniques
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Federal Committee on Statistical Methodology: Report on Statistical Disclosure Limitation Methodology(Working Paper No. 22)
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Future of Privacy Forum: A Visual Guide to Practical Data De-Identification
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The Royal Society: Protecting Privacy in Practice
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Song, Dahlmeier, & Bressan 2014: Not so unique in the crowd: A simple and effective algorithm for anonymizing location data
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Austin, TX: Dockless Data API
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Santa Monica, CA: MDS Provider Toolkit
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Los Angeles, CA: MDS Core
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Los Angeles, CA: MDS Data Validator
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SharedStreets: Mobility Metrics
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Blue Systems: MDS Validator Tools
Toolkits and resources for understanding and managing risk associated with mobility data.
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Seattle, WA & Future of Privacy Forum: Open Data Privacy Risk Assessment (see especially Appendix C)
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San Francisco, CA: DataSF, Open Data Release Toolkit
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Future of Privacy Forum: Privacy Risk Assessment for Smart and Connected Communities
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Open Data Institute: Data Ethics Canvas
Open / public mobility data sets, and information about approaches to anonymization.
| Entity | Dataset | Anonymization Method(s) | Geography |
|---|---|---|---|
| Austin, TX | Shared Micromobility Vehicle Trips | Timestamps rounded to nearest 15-min | Polygons: origin/destination census tract |
| Calgary, Alberta | Shared Mobility Pilot Trips | Timestamps rounded to nearest hour | Points: origin/destination centroids of custom hex fishnet. Lines: origin/destination street segment |
| Chicago, IL | E-Scooter Trips | Timestamps rounded to nearest hour | Points: origin/destination census tract centroid; minimum three trips present at start and end tract/time. |
| Kansas City, MO | Microtransit (Scooter and Ebike) Trips | Timestamps rounded to nearest 15-min | Points: origin/destination truncated to three decimal places |
| Louisville, KY | Dockless Vehicle Trips | Timestamps rounded to nearest 15-min, k-anonymity for infrequent O/D pairs | Points: origin/destination truncated to three decimal places (two decimals for infrequent O/D pairs) |
| Minneapolis, MN | Motorized Foot Scooter Trips and Availability by year | Timestamps rounded to nearest 30-min | Lines: origin/destination street segment |
| Portland, OR | E-Scooter Trips | Timestamps rounded to nearest hour, day of month not known | Polygons: origin/destination census block groups |
| Ride Report | Open Data Dashboard (multiple cities) | Dates/times aggregated by quarter | Lines: trip counts by street segment |
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Austin, TX: Explore Dockless Data With Us
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Chicago, IL: How Chicago Protects Privacy in TNP and Taxi Open Data
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Louisville, KY: Open Data Publishing Methodology
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Portland, OR: Managing Mobility Data
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Berkman Klein Center: Open Data Privacy Playbook
Public-facing mobility data visualization and reporting tools.
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Austin, TX: Micromobility Data Explorer / Micromobility Program Reporting Dashboard
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Kansas City, MO: Scooter & E-Bike Heatmap
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Louisville, KY: Dockless Vehicle Origin & Destination Map
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Minneapolis, MN: Scooter compliance dashboard
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Portland, OR: E-Scooter Trips Dashboard and Interactive street segment map
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Seattle, WA: Mobility Dashboards
Resources for public education and outreach related to mobility data and privacy.
- Future of Privacy Forum: Shedding Light on Smart City Privacy
