Recommendations for big data programs at transportation agencies

Gregory D. Erhardt, Michael Batty, Elsa Arcaute

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Big data that record mobility patterns have the potential to provide important insight to transportation agencies about how to better plan and operate the transportation system. Those agencies often already have access to valuable data assets, but faced with limited resources and a lack of experience working with emerging data sources and methods, those data may go under-utilized. In the case of real-time data feeds, the data may be lost altogether if they are not archived. This paper provides recommendations for planning and establishing big data programs at transportation agencies. These recommendations are derived from the lessons learned during the development of a big data fusion tool for measuring transportation system changes in San Francisco. It focuses on broad data management issues that staff at a public agency may face, such as identifying and prioritizing data sources and uses, managing privacy considerations and data sharing policies, and addressing data issues that may arise in contracting situations.

Original languageEnglish
Title of host publicationBig Data for Regional Science
Number of pages12
ISBN (Electronic)9781351983266
StatePublished - Jan 1 2017

Bibliographical note

Publisher Copyright:
© 2018 selection and editorial matter, Laurie A. Schintler and Zhenhua Chen.

ASJC Scopus subject areas

  • General Economics, Econometrics and Finance
  • General Business, Management and Accounting


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