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Overview

Data Science for Transportation is a journal focused on the application of data science methods in the field of transportation.

  • Encourages a cross-disciplinary dialogue with original research articles, review papers, and commentary articles.
  • Showcases the latest methodological advances and their implications for policy making.
  • Highlights the significant impact of these fields on other scientific disciplines and various aspects of society and industry.
  • Focuses on analytical data-driven methods and high-quality application-based studies.
  • Discusses emerging ethical, social, and privacy issues in this domain.

Co-Editors-in-Chief
  • Satish V Ukkusuri,
  • Leclercq Ludovic
Submission to first decision (median)
16 days
Downloads
37,831 (2023)

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Journal information

Electronic ISSN
2948-1368
Print ISSN
2948-135X
Abstracted and indexed in
  1. ACM Digital Library
  2. Baidu
  3. CLOCKSS
  4. CNKI
  5. CNPIEC
  6. Dimensions
  7. EBSCO
  8. Google Scholar
  9. INSPEC
  10. Japanese Science and Technology Agency (JST)
  11. Naver
  12. OCLC WorldCat Discovery Service
  13. Portico
  14. ProQuest
  15. TD Net Discovery Service
  16. Transport Research International Documentation(TRID)
  17. Wanfang
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© Springer Nature Singapore Pte Ltd.

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