Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-30330Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Doemer, Manuel | - |
| dc.contributor.author | Kempf, David | - |
| dc.date.accessioned | 2024-03-22T10:09:08Z | - |
| dc.date.available | 2024-03-22T10:09:08Z | - |
| dc.date.issued | 2023-06-21 | - |
| dc.identifier.issn | 2363-9881 | de_CH |
| dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/30330 | - |
| dc.description.abstract | The primary challenge of data science as a new paradigm of scientific discovery is the rigorous and practically usable documentation of the data product development process. A more expanding and consequent implementation of principles from modern software development and operations will allow the field to mature as a truly scientific discipline. | de_CH |
| dc.language.iso | en | de_CH |
| dc.publisher | KIT Scientific Publishing | de_CH |
| dc.relation.ispartof | Archives of Data Science, Series A | de_CH |
| dc.rights | http://creativecommons.org/licenses/by-sa/4.0/ | de_CH |
| dc.subject | Science of data science | de_CH |
| dc.subject | ISSDS 2021 | de_CH |
| dc.subject | Data science | de_CH |
| dc.subject.ddc | 005: Computerprogrammierung, Programme und Daten | de_CH |
| dc.title | Is it ops that make data science scientific? | de_CH |
| dc.type | Beitrag in wissenschaftlicher Zeitschrift | de_CH |
| dcterms.type | Text | de_CH |
| zhaw.departement | School of Engineering | de_CH |
| zhaw.organisationalunit | Institute of Computational Physics (ICP) | de_CH |
| dc.identifier.doi | 10.5445/IR/1000150238 | de_CH |
| dc.identifier.doi | 10.21256/zhaw-30330 | - |
| zhaw.funding.eu | No | de_CH |
| zhaw.issue | 2 | de_CH |
| zhaw.originated.zhaw | Yes | de_CH |
| zhaw.pages.end | 17 | de_CH |
| zhaw.pages.start | 1 | de_CH |
| zhaw.publication.status | publishedVersion | de_CH |
| zhaw.volume | 8 | de_CH |
| zhaw.publication.review | Peer review (Publikation) | de_CH |
| zhaw.author.additional | No | de_CH |
| zhaw.display.portrait | Yes | de_CH |
| Appears in collections: | Publikationen School of Engineering | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2023_Doemer-Kempf_Data-Science-Ops.pdf | 246.45 kB | Adobe PDF |  View/Open |
Show simple item record
Doemer, M., & Kempf, D. (2023). Is it ops that make data science scientific? Archives of Data Science, Series A, 8(2), 1–17. https://doi.org/10.5445/IR/1000150238
Doemer, M. and Kempf, D. (2023) ‘Is it ops that make data science scientific?’, Archives of Data Science, Series A, 8(2), pp. 1–17. Available at: https://doi.org/10.5445/IR/1000150238.
M. Doemer and D. Kempf, “Is it ops that make data science scientific?,” Archives of Data Science, Series A, vol. 8, no. 2, pp. 1–17, Jun. 2023, doi: 10.5445/IR/1000150238.
DOEMER, Manuel und David KEMPF, 2023. Is it ops that make data science scientific? Archives of Data Science, Series A. 21 Juni 2023. Bd. 8, Nr. 2, S. 1–17. DOI 10.5445/IR/1000150238
Doemer, Manuel, and David Kempf. 2023. “Is It Ops That Make Data Science Scientific?” Archives of Data Science, Series A 8 (2): 1–17. https://doi.org/10.5445/IR/1000150238.
Doemer, Manuel, and David Kempf. “Is It Ops That Make Data Science Scientific?” Archives of Data Science, Series A, vol. 8, no. 2, June 2023, pp. 1–17, https://doi.org/10.5445/IR/1000150238.
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