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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. 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.
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    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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