CRMay 16, 2017

Differentially Private Release of Public Transport Data: The Opal Use Case

arXiv:1705.05957v12 citations
Originality Synthesis-oriented
AI Analysis

This addresses privacy concerns for public transport users and agencies by enabling data sharing without compromising individual privacy, though it is incremental as it applies existing methods to a new dataset.

The paper tackled the problem of releasing public transport usage data while preserving privacy by applying a differentially private algorithm to tap-on/tap-off data from Transport for New South Wales, resulting in a privacy-preserving dataset for analysis.

This document describes the application of a differentially private algorithm to release public transport usage data from Transport for New South Wales (TfNSW), Australia. The data consists of two separate weeks of "tap-on/tap-off" data of individuals who used any of the four different modes of public transport from TfNSW: buses, light rail, train and ferries. These taps are recorded through the smart ticketing system, known as Opal, available in the state of New South Wales, Australia.

Foundations

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