A Functioning Beta Solution to the Challenge of Opening Transit Payment System Transaction Data

TL;DR

This paper presents a privacy-preserving anonymization scheme for transit fare transaction data from the San Francisco Bay Area's Clipper system, aiming to balance data utility with customer privacy.

Contribution

The paper introduces a novel anonymizing scheme tailored for transit transaction data that addresses privacy concerns while maintaining data usability.

Findings

Scheme effectively anonymizes transit data

Balances privacy protection with data utility

Invites community feedback on approach

Abstract

The deployment of smart-card-based public transit fare payment systems provides government the opportunity to create a valuable derivative data product. Companies such as Urban Engines have demonstrated an ability to add value to the data derived from transit fare transactions. The challenge for the public sector is to, for the societal good, leverage private sector interest by giving access to useful fare transaction data in a manner that protects customer privacy. This challenge is particularly acute in California, where privacy laws make sharing data in a manner that supports the public interest difficult. This paper presents the Metropolitan Transportation Commission's (MTC's) proposed solution to the problem. MTC operates the Clipper(r) transit fare payment system for the San Francisco Bay Area. In an effort to share usable data that protects customer privacy, MTC developed an anonymizing scheme that is the subject of the present paper. We seek feedback on our approach from the Data for Good Exchange community, asking: in seeking a balance between customer privacy and usability, does the scheme go too far in either direction? And, should we take a different anonymizing approach?