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Mining Open Government Data Used in Scientific Research

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Transforming Digital Worlds (iConference 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10766))

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Abstract

In the following paper, we describe results from mining citations, mentions, and links to open government data (OGD) in peer-reviewed literature. We inductively develop a method for categorizing how OGD are used by different research communities, and provide descriptive statistics about the publication years, publication outlets, and OGD sources. Our results demonstrate that, 1. The use of OGD in research is steadily increasing from 2009 to 2016; 2. Researchers use OGD from 96 different open government data portals, with data.gov.uk and data.gov being the most frequent sources; and, 3. Contrary to previous findings, we provide evidence suggesting that OGD from developing nations, notably India and Kenya, are being frequently used to fuel scientific discoveries. The findings of this paper contribute to ongoing research agendas aimed at tracking the impact of open government data initiatives, and provides an initial description of how open government data are valuable to diverse scientific research communities.

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Notes

  1. 1.

    https://www.data.gov/open-gov/.

  2. 2.

    https://www.elsevier.com/solutions/scopus/content.

  3. 3.

    https://data.gov.uk/dataset/index-of-multiple-deprivation.

  4. 4.

    https://data.cityofchicago.org/public-safety/crimes-2001-to-present/ijzp-q8t2.

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Acknowledgement

This research was supported in part by IMLS grant # RE-40-16-0015-16. Supporting data and in-depth explanation of the methods used in this study can be found at https://github.com/OpenDataLiteracy/iConference_2018.

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Correspondence to An Yan .

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Yan, A., Weber, N. (2018). Mining Open Government Data Used in Scientific Research. In: Chowdhury, G., McLeod, J., Gillet, V., Willett, P. (eds) Transforming Digital Worlds. iConference 2018. Lecture Notes in Computer Science(), vol 10766. Springer, Cham. https://doi.org/10.1007/978-3-319-78105-1_34

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  • DOI: https://doi.org/10.1007/978-3-319-78105-1_34

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