Research Usage and Social Impact of Crowdsourced Air Traffic Data

Crowdsourced data have played an increasing role in research in the sciences over the past decades. From their early instantiations in the 1990s to the search for extraterrestrial intelligence, the concepts of crowdsourcing and citizen science have gained renewed popularity with the broad availability of big data systems. The OpenSky Network has been a poster child of the successful use of crowdsourced data in research and citizen science for many years, with more than 150 peer-reviewed publications using its data. In this article, we follow the efforts made and the results achieved by the OpenSky Network as a non-profit organization with the mission to advance research in and around aviation. We examine the backgrounds and typical usage patterns of OpenSky’s users, both academic and non-academic. We further look at the social impact of air traffic data, particularly during the COVID-19 crisis, and finally examine ways to improve some existing gaps in the data.

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Crowdsourced Air Traffic Data from the OpenSky Network 2019–20

10.5194/essd-2020-223 ◽

2020 ◽

Author(s):

Martin Strohmeier ◽

Xavier Olive ◽

Jannis Lübbe ◽

Matthias Schäfer ◽

Vincent Lenders

Keyword(s):

Traffic Control ◽

Weather Forecasting ◽

Air Traffic ◽

Traffic Data ◽

Control Data ◽

Non Profit ◽

The Past ◽

Containment Measures ◽

Climate Analysis ◽

First Time

Abstract. The OpenSky Network is a non-profit association that crowdsources the global collection of live air traffic control data broadcast by airplanes and makes it available to researchers. OpenSky's data has been used by over a hundred academic groups in the past five years, with popular research applications ranging from improved weather forecasting to climate analysis. With the COVID-19 outbreak, the demand for live and historic aircraft flight data has surged further. Researchers around the world use air traffic data to comprehend the spread of the pandemic and analyze the effects of the global containment measures on economies, climate and other systems. With this work, we present a comprehensive air traffic dataset, derived and enriched from the full OpenSky data and made publicly available for the first time (Olive et al. (2020), DOI: https://doi.org/10.5281/zenodo.3928564). It spans all flights seen by the network's more than 3000 members between 1 January 2019 and 1 July 2020. Overall, the archive includes 41 900 660 flights, from 160 737 aircraft, which were seen to frequent 13 934 airports in 127 countries.

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Crowdsourced air traffic data from the OpenSky Network 2019–2020

Earth System Science Data ◽

10.5194/essd-13-357-2021 ◽

2021 ◽

Vol 13 (2) ◽

pp. 357-366

Author(s):

Martin Strohmeier ◽

Xavier Olive ◽

Jannis Lübbe ◽

Matthias Schäfer ◽

Vincent Lenders

Keyword(s):

Traffic Control ◽

Weather Forecasting ◽

Air Traffic ◽

Traffic Data ◽

Control Data ◽

Non Profit ◽

The Past ◽

Containment Measures ◽

Climate Analysis ◽

First Time

Abstract. The OpenSky Network is a non-profit association that crowdsources the global collection of live air traffic control data broadcast by aircraft and makes them available to researchers. OpenSky's data have been used by over 100 academic groups in the past 5 years, with popular research applications ranging from improved weather forecasting to climate analysis. With the COVID-19 outbreak, the demand for live and historic aircraft flight data has surged. Researchers around the world use air traffic data to comprehend the spread of the pandemic and analyse the effects of the global containment measures on economies, climate and other systems. With this work, we present a comprehensive air traffic dataset, derived and enriched from the full OpenSky data and made publicly available for the first time (Olive et al., 2020; https://doi.org/10.5281/zenodo.3931948, last access: 9 February 2021). It spans all flights seen by the network's more than 3500 members between 1 January 2019 and 1 July 2020. The archive is being updated every month and for the first 18 months includes 41 900 660 flights, from 160 737 aircraft, which were seen to frequent 13 934 airports in 127 countries.

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Research on Knowledge Management Models at Universities Using Fuzzy Analytic Hierarchy Process (FAHP)

Sustainability ◽

10.3390/su13020809 ◽

2021 ◽

Vol 13 (2) ◽

pp. 809

Author(s):

Ngoc Thach Pham ◽

Anh Duc Do ◽

Quang Vinh Nguyen ◽

Van Loi Ta ◽

Thi Thanh Binh Dao ◽

...

Keyword(s):

Knowledge Management ◽

Analytic Hierarchy Process ◽

Fuzzy Analytic Hierarchy Process ◽

Data Systems ◽

Knowledge Use ◽

Analytic Hierarchy ◽

Priority Order ◽

Big Data Systems ◽

Document Review ◽

Hierarchy Process

This study aims to investigate and evaluate factors related to the knowledge management model at universities in Hanoi, Vietnam. Based on the system literature review (SLR) approach, the study follows descriptive and inductive approach results of the document review process. Eight factors were synthesized with the fuzzy analytic hierarchy process (FAHP) to evaluate the priority order. Ten experts from seven universities participated in the survey. The results rank as follows: (1) knowledge sharing factor (this also has the highest best nonfuzzy performance (BNP) and average multiplier weight (GM)); (2) knowledge management with big data systems; (3) knowledge creation; (4) knowledge use; (5) knowledge gathering; (6) leadership; (7) knowledge rating; and (8) knowledge storage. Discussions, conclusions, limitations of the study, and suggestions for future studies are also mentioned in this study.

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