Reuse, Reduce, Support: Design Principles for Green Data Mining
| dc.contributor.author | Schneider, Johannes | |
| dc.contributor.author | Seidel, Stefan | |
| dc.contributor.author | Basalla, Marcus | |
| dc.contributor.author | Brocke, Jan | |
| dc.date.accessioned | 2023-02-27T10:50:56Z | |
| dc.date.available | 2023-02-27T10:50:56Z | |
| dc.date.issued | 2023 | |
| dc.description.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. | de |
| dc.identifier.doi | 10.1007/s12599-022-00780-w | |
| dc.identifier.pissn | 1867-0202 | |
| dc.identifier.uri | http://dx.doi.org/10.1007/s12599-022-00780-w | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/40415 | |
| dc.publisher | Springer | |
| dc.relation.ispartof | Business & Information Systems Engineering: Vol. 65, No. 1 | |
| dc.relation.ispartofseries | Business & Information Systems Engineering | |
| dc.subject | Data mining||Design principles||Design science research||Energy efficiency||Energy-saving||Green Data Science||Green IS||Green IT | |
| dc.title | Reuse, Reduce, Support: Design Principles for Green Data Mining | de |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 83 | |
| gi.citation.startPage | 65 |