The journal will publish original research papers applying big data techniques to transportation problems. The problems big data techniques are applied to can range from improvement in real-time transportation operations, transportation planning to near term prediction of crash risk. The paper may provide novel ideas about improved data ingestion, data curation, data archiving, data visualization, data security etc. for better transportation decision making. The data being used in the paper should at least satisfy on of the 3 V’s of the Gartner’s definition of big data i.e., high volume, high velocity or high variety. Also, knowledge discovery should use holistic approach instead of sampling and aggregation techniques to be considered as big data application.
Editor-in-Chief
  • Adel W. Sadek,
  • Anuj Sharma
Publishing model
Hybrid. Open Choice – What is this?

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About this journal

Electronic ISSN
2523-3564
Print ISSN
2523-3556
Abstracted and indexed in
  1. ACM Digital Library
  2. EBSCO Discovery Service
  3. Google Scholar
  4. INSPEC
  5. Institute of Scientific and Technical Information of China
  6. Japanese Science and Technology Agency (JST)
  7. Naver
  8. OCLC WorldCat Discovery Service
  9. ProQuest-ExLibris Primo
  10. ProQuest-ExLibris Summon
  11. Transport Research International Documentation(TRID)
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