Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen: http://dx.doi.org/10.25673/103285
Langanzeige der Metadaten
DC ElementWertSprache
dc.contributor.authorSchulz, Michael-
dc.contributor.authorNeuhaus, Uwe-
dc.contributor.authorKühnel, Stephan-
dc.contributor.authorRohde, Heiko-
dc.contributor.authorHoseini, Sayed-
dc.contributor.authorTheuerkauf, René-
dc.date.accessioned2023-05-12T12:51:30Z-
dc.date.available2023-05-12T12:51:30Z-
dc.date.issued2023-02-
dc.identifier.urihttps://opendata.uni-halle.de//handle/1981185920/105237-
dc.identifier.urihttp://dx.doi.org/10.25673/103285-
dc.description.abstractThe development of the DASC-PM (Data Science Process Model) is based on the knowledge of a large working group consisting of experts in Data Science. We believe that the procedure described in the DASC-PM can be used beneficially in data-driven projects and offers support in structuring complex projects. In version 1.1 of the DASC-PM, which was published in German in March 2022 and in English in June 2022, we significantly revised the original documentation based on feedback from readers. We hope that the new document is easier to understand and more structured than the previous one, thus reducing the barriers to using the process model for the first time. With this publication, we realize another suggestion of the readers: a collection of case studies in which the DASC-PM is applied. On the one hand, the documentation of the DASC-PM claims to show the procedure of a Data Science project as detailed as possible. On the other hand, however, it is also intended to ensure universality, which is reflected in a thoroughly broad spectrum of applications. Showing examples of the direct application and usability of DASC-PM in different application domains represents another aspect that is intended to reduce the aforementioned application barriers. This collection of case studies is intended to provide readers with guidance on the use of DASC-PM. This use is presented from different perspectives and at very different levels of abstraction. Thereby, projects from practice and science are considered. We thank all authors of the case studies for their commitment to the working group and are very pleased to see the exciting contributions that have emerged. However, the present collection of case studies should not be seen as complete. We are always interested in your feedback on the use of DASC-PM in practical or scientific projects and would also be happy to add your case study to our collection. If you are interested in joining our working group or would like us to keep you informed about current developments regarding the DASC-PM, feel free to get in touch at the contact address below. Elmshorn, Flensburg, Halle (Saale), Hamburg, and Krefeld in February 2023 The DASC-PM Core Team Contact: info@dasc-pm.orgeng
dc.description.sponsorshipSupported by the NORDAKADEMIE foundation-
dc.language.isoeng-
dc.publisherUniversitäts- und Landesbibliothek Sachsen-Anhalt-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectData Scienceeng
dc.subjectProcess Model-
dc.subjectprocedure model-
dc.subjectproject model-
dc.subjectcase studies-
dc.subject.ddcDDC::0** Informatik, Informationswissenschaft, allgemeine Werke-
dc.subject.ddcData Science-
dc.subject.ddcCase Studies-
dc.titleDASC-PM v1.1 Case Studieseng
dc.typeBook-
local.versionTypepublishedVersion-
local.openaccesstrue-
local.accessrights.dnbfree-
Enthalten in den Sammlungen:Lehrstuhl für Betriebliches Informationsmanagement

Dateien zu dieser Ressource:
Datei Beschreibung GrößeFormat 
DASC-PM_CaseStudies.pdf1.38 MBAdobe PDFMiniaturbild
Öffnen/Anzeigen