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Towards open government through open source software for web analytics: The case of Matomo
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Software Systems Research Group (SSRG))ORCID iD: 0000-0003-2700-2535
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Software Systems Research Group (SSRG))ORCID iD: 0000-0002-2825-135X
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Software Systems Research Group (SSRG))ORCID iD: 0000-0002-6215-3753
Combitech AB, Skövde, Sweden.ORCID iD: 0000-0002-2161-164x
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2021 (English)In: eJournal of eDemocracy & Open Government, E-ISSN 2075-9517, Vol. 13, no 2, p. 133-153Article in journal (Refereed) Published
Abstract [en]

Web analytics technologies provide opportunities for organisations to obtain information about users visiting their websites in order to understand and optimise web usage. Use of such technologies often leads to issues related to data privacy and potential lock-in to specific suppliers and proprietary technologies. Use of open source software (OSS) for web analytics can create conditions for avoiding issues related to data privacy and lock-in, and thereby provides opportunities for a long-term sustainable solution for organisations both in the public and private sectors. This paper characterises use of and engagement with OSS projects for web analytics. Specifically, we contribute a characterisation of use of OSS licensed web analytics technologies in Swedish government authorities, and a characterisation of organisational engagement with the Matomo OSS project for web analytics.

Place, publisher, year, edition, pages
Krems: Department for E-Governance and Administration, Danube University Krems , 2021. Vol. 13, no 2, p. 133-153
Keywords [en]
Open source software, web analytics, government authorities, Matomo
National Category
Computer and Information Sciences
Research subject
INF304 Open Source; Software Systems Research Group (SSRG)
Identifiers
URN: urn:nbn:se:his:diva-20995DOI: 10.29379/jedem.v13i2.650Scopus ID: 2-s2.0-85131351814OAI: oai:DiVA.org:his-20995DiVA, id: diva2:1646255
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CC BY 3.0

Available from: 2022-03-21 Created: 2022-03-21 Last updated: 2022-06-17Bibliographically approved

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Gamalielsson, JonasLundell, BjörnButler, SimonBrax, Christoffer

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