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Examining Interest in Open Government Data Through Digital Traces

  • Conference paper
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Information for a Better World: Normality, Virtuality, Physicality, Inclusivity (iConference 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13972))

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Abstract

The benefits that open government data (OGD) may hold for society are plentiful, including increased government transparency and economic growth. To realize these benefits, users must access and transform OGD to create value. Yet, the increasingly widespread provision of OGD has not necessarily spurred abundant uses nor has it attracted a multitude of users. To support the expansion of uses and users, research about OGD has turned to examination of data provision and users’ intentions to engage with OGD. A complementary approach to characterize actual demand for OGD has received little attention. In our exploratory study, we take a snapshot of the most viewed items on the OGD portals of the fifty most populous US cities to investigate naturalistically the topics and types of items apparently attracting user interest. We draw implications for OGD research and practice from our preliminary analysis of highly viewed items.

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Notes

  1. 1.

    List drawn from the US Census Bureau City and Town Population Totals: 2020–2021 https://www.census.gov/data/tables/time-series/demo/popest/2020s-total-cities-and-towns.html.

  2. 2.

    We find the relative comparison of item topics and types more meaningful than absolute comparison of view counts. Portals using Socrata and ArcGIS software generally had higher view counts for most viewed items than those using CKAN; however, this likely reflects differing user actions that the software counts as a view.

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Correspondence to Caroline Stratton .

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Stratton, C., Hussain, S. (2023). Examining Interest in Open Government Data Through Digital Traces. In: Sserwanga, I., et al. Information for a Better World: Normality, Virtuality, Physicality, Inclusivity. iConference 2023. Lecture Notes in Computer Science, vol 13972. Springer, Cham. https://doi.org/10.1007/978-3-031-28032-0_34

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  • DOI: https://doi.org/10.1007/978-3-031-28032-0_34

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