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Reuse, Reduce, Support: Design Principles for Green Data Mining

Author

Listed:
  • Johannes Schneider

    (University of Liechtenstein)

  • Stefan Seidel

    (University of Liechtenstein)

  • Marcus Basalla

    (University of Liechtenstein)

  • Jan Brocke

    (University of Liechtenstein)

Abstract

This paper reports on a design science research (DSR) study that develops design principles for “green” – more environmentally sustainable – data mining processes. Grounded in the Cross Industry Standard Process for Data Mining (CRISP-DM) and on a review of relevant literature on data mining methods, Green IT, and Green IS, the study identifies eight design principles that fall into the three categories of reuse, reduce, and support. The paper develops an evaluation strategy and provides empirical evidence for the principles’ utility. It suggests that the results can inform the development of a more general approach towards Green Data Science and provide a suitable lens to study sustainable computing.

Suggested Citation

  • Johannes Schneider & Stefan Seidel & Marcus Basalla & Jan Brocke, 2023. "Reuse, Reduce, Support: Design Principles for Green Data Mining," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(1), pages 65-83, February.
    • Handle: RePEc:spr:binfse:v:65:y:2023:i:1:d:10.1007_s12599-022-00780-w
    DOI: 10.1007/s12599-022-00780-w
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    References listed on IDEAS

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    1. Stefan Seidel & Leona Chandra Kruse & Nadine Székely & Michael Gau & Daniel Stieger & Ken Peffers & Tuure Tuunanen & Björn Niehaves & Kalle Lyytinen, 2018. "Design principles for sensemaking support systems in environmental sustainability transformations," European Journal of Information Systems, Taylor & Francis Journals, vol. 27(2), pages 221-247, March.
    2. Hendrik Hilpert & Johann Kranz & Matthias Schumann, 2013. "Leveraging Green IS in Logistics," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(5), pages 315-325, October.
    3. Leena Suhl & Stefan Voß, 2014. "An Introduction to the Special Focus Issue “Decision Analytics”," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(3), pages 129-130, June.
    4. Panos Vassiliadis, 2009. "A Survey of Extract–Transform–Load Technology," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 5(3), pages 1-27, July.
    5. Joseph G. Walls & George R. Widmeyer & Omar A. El Sawy, 1992. "Building an Information System Design Theory for Vigilant EIS," Information Systems Research, INFORMS, vol. 3(1), pages 36-59, March.
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