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

Johannes Schneider (), Stefan Seidel (), Marcus Basalla () and Jan Brocke ()
Additional contact information
Johannes Schneider: University of Liechtenstein
Stefan Seidel: University of Liechtenstein
Marcus Basalla: University of Liechtenstein
Jan Brocke: University of Liechtenstein

Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, 2023, vol. 65, issue 1, No 5, 65-83

Abstract: 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.

Keywords: Green Data Science; Green IT; Green IS; Data mining; Energy efficiency; Energy-saving; Design science research; Design principles (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s12599-022-00780-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:binfse:v:65:y:2023:i:1:d:10.1007_s12599-022-00780-w

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/12599

DOI: 10.1007/s12599-022-00780-w

Access Statistics for this article

Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK is currently edited by Martin Bichler

More articles in Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK from Springer, Gesellschaft für Informatik e.V. (GI)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().