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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-24611
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dc.contributor.authorStadelmann, Thilo-
dc.contributor.authorKlamt, Tino-
dc.contributor.authorMerkt, Philipp H.-
dc.date.accessioned2022-03-17T09:27:47Z-
dc.date.available2022-03-17T09:27:47Z-
dc.date.issued2022-03-10-
dc.identifier.issn2363-9881de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/24611-
dc.description.abstractData science is one of the most significant developments in computing in the 21st century. It is also described as a discipline in the making, drawing principles, methods and tools from established fields like computer science, statistics, science, business, politics, and any domain with adequate data. What are data science’s underlying principles and techniques (models, methods) that are applicable across different use cases and fields of application? What novel aspect of science underlies this emerging discipline? We argue that it is data centrism - the reliance on data itself, in mindset, methods and products - that makes data science more than the sum of its parts, as this is not done in any other discipline.de_CH
dc.language.isoende_CH
dc.publisherKIT Scientific Publishingde_CH
dc.relation.ispartofArchives of Data Science, Series Ade_CH
dc.rightshttp://creativecommons.org/licenses/by-sa/4.0/de_CH
dc.subjectScience of data sciencede_CH
dc.subjectISSDS 2021de_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.titleData centrism and the core of Data Science as a scientific disciplinede_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitCentre for Artificial Intelligence (CAI)de_CH
dc.identifier.doi10.5445/IR/1000143637de_CH
dc.identifier.doi10.21256/zhaw-24611-
zhaw.funding.euNode_CH
zhaw.issue2de_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.volume8de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedMachine Perception and Cognitionde_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedZHAW digitalde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Stadelmann, T., Klamt, T., & Merkt, P. H. (2022). Data centrism and the core of Data Science as a scientific discipline. Archives of Data Science, Series A, 8(2). https://doi.org/10.5445/IR/1000143637
Stadelmann, T., Klamt, T. and Merkt, P.H. (2022) ‘Data centrism and the core of Data Science as a scientific discipline’, Archives of Data Science, Series A, 8(2). Available at: https://doi.org/10.5445/IR/1000143637.
T. Stadelmann, T. Klamt, and P. H. Merkt, “Data centrism and the core of Data Science as a scientific discipline,” Archives of Data Science, Series A, vol. 8, no. 2, Mar. 2022, doi: 10.5445/IR/1000143637.
STADELMANN, Thilo, Tino KLAMT und Philipp H. MERKT, 2022. Data centrism and the core of Data Science as a scientific discipline. Archives of Data Science, Series A. 10 März 2022. Bd. 8, Nr. 2. DOI 10.5445/IR/1000143637
Stadelmann, Thilo, Tino Klamt, and Philipp H. Merkt. 2022. “Data Centrism and the Core of Data Science as a Scientific Discipline.” Archives of Data Science, Series A 8 (2). https://doi.org/10.5445/IR/1000143637.
Stadelmann, Thilo, et al. “Data Centrism and the Core of Data Science as a Scientific Discipline.” Archives of Data Science, Series A, vol. 8, no. 2, Mar. 2022, https://doi.org/10.5445/IR/1000143637.


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