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Reviewing the DATAS of aviation research data: Diversity, availability, tractability, applicability, and sources

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  • Li, Max Z.
  • Ryerson, Megan S.

Abstract

The field of aviation research is entering the era of big data. While data-driven advancements in aviation have clearly brought about applicable models and results with immediate implications, we argue that the influx of aviation data should be better characterized and documented to enable more efficient and standardized usage. To this end, we examine 200 well-cited research articles from sub-disciplines ranging from revenue management to air traffic control published on or after 2010 in order to analyze the diversity, availability, tractability, applicability, and sources (DATAS) of data utilized in aviation research. We find high levels of data diversity within aviation research, with 16 data categories ranging from air traffic flow management-type data to data from distributed sensors in line with the Internet-of-Things (IoT) paradigm. We identified a dominance of proprietary, non-public data in aviation research, with 68% of the 200 research articles utilizing solely proprietary data in deriving their results, and a further 8% utilizing a mixture of proprietary and publicly available data. The pervasiveness of proprietary data has implications on reproducibility and extending research results. We also highlight the increasing tractability of the data by surveying the computational power required to process the data sets, and present vignettes of applications and results that stem from these data-driven studies. Finally, we propose several recommendations regarding standardizing data source nomenclature as well as increasing the availability of and usage of publicly available data.

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  • Li, Max Z. & Ryerson, Megan S., 2019. "Reviewing the DATAS of aviation research data: Diversity, availability, tractability, applicability, and sources," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 111-130.
    • Handle: RePEc:eee:jaitra:v:75:y:2019:i:c:p:111-130
    DOI: 10.1016/j.jairtraman.2018.12.004
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    1. Frédéric Dobruszkes & Didier Peeters, 2019. "The magnitude of detours faced by commercial flights: A global assessment," ULB Institutional Repository 2013/293811, ULB -- Universite Libre de Bruxelles.
    2. Sofia Pinheiro Melo & Alexander Barke & Felipe Cerdas & Christian Thies & Mark Mennenga & Thomas S. Spengler & Christoph Herrmann, 2020. "Sustainability Assessment and Engineering of Emerging Aircraft Technologies—Challenges, Methods and Tools," Sustainability, MDPI, vol. 12(14), pages 1-27, July.
    3. Dobruszkes, Frédéric & Peeters, Didier, 2019. "The magnitude of detours faced by commercial flights: A global assessment," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    4. Ma, Hoi-Lam & Sun, Yige & Chung, Sai-Ho & Chan, Hing Kai, 2022. "Tackling uncertainties in aircraft maintenance routing: A review of emerging technologies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    5. Li, Max Z. & Ryerson, Megan S. & Balakrishnan, Hamsa, 2019. "Topological data analysis for aviation applications," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 149-174.
    6. Christopher L. Atkinson, 2020. "The Federal Aviation Administration Airport Improvement Program: Who Benefits?," Public Organization Review, Springer, vol. 20(4), pages 789-805, December.

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