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Challenge 4: Optimizing Rider Data

Michael Caprio edited this page Sep 15, 2023 · 8 revisions

Enrich Rider-Focused Datasets To Enable Useful Applications

Background

There is a lack of comprehensive data on rider demographics and the prospect of coordinating transit service with the needs of large employers is challenging.

Federal programming provides funding to fill gaps in transit service, but some organizations have underutilized the vehicles acquired through these means. Statistics utilized to assess funding do not necessarily equate to needs.

The Challenge

There is a pronounced need for better connections between different transit systems to address low ridership and the challenges of providing frequent service without incurring undue costs. Through effective planning, data aggregation, and coordination many stakeholders might benefit. An API that serves up this data could empower many different kinds of applications - but considerations of rider privacy and security of data should be thought of as well.


Solutions

A first step would be compiling demographic profiles of riders in the region. Some material exists in the in the wiki here, but there could be much more added to this by collating data from other federal, state, and local resources listed in Online Resources And Data Sets.


Resources

  • tk

Challenge owners: ** ** and ** **

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