- AutorIn
- Roy Meissner Universität Leipzig, Fakultät für Mathematik und Informatik, Institut für Informatik
- Kurt JunghannsUniversität Leipzig, Fakultät für Mathematik und Informatik, Institut für Informatik
- Titel
- Using DevOps principles to continuously monitor RDF data quality
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa2-159401
- Quellenangabe
- SEMANTiCS 2016 : Proceedings of the 12th International Conference on Semantic Systems#Leipzig, Germany - September 12 - 15, 2016
Erscheinungsort: Leipzig
Erscheinungsjahr: 2016
Seiten: 189-192
ISBN: 978-1-4503-4752-5
DOI: 10.1145/2993318.2993351 - Erstveröffentlichung
- 2016
- Abstract (EN)
- One approach to continuously achieve a certain data quality level is to use an integration pipeline that continuously checks and monitors the quality of a data set according to defined metrics. This approach is inspired by Continuous Integration pipelines, that have been introduced in the area of software development and DevOps to perform continuous source code checks. By investigating in possible tools to use and discussing the specific requirements for RDF data sets, an integration pipeline is derived that joins current approaches of the areas of software development and semantic web as well as reuses existing tools. As these tools have not been built explicitly for CI usage, we evaluate their usability and propose possible workarounds and improvements. Furthermore, a real world usage scenario is discussed, outlining the benefit of the usage of such a pipeline.
- Andere Ausgabe
- Using DevOps principles to continuously monitor RDF data quality
Link: http://delivery.acm.org/10.1145/3000000/2993351/p189-meissner.pdf?ip=139.18.24.114&id=2993351&acc=ACTIVE%20SERVICE&key=2BA2C432AB83DA15%2E54D814AD3CCF228A%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=792635225&CFTOKEN=89949651&__acm__=1501658389_cb2ce25a024be3ff752629ffdbe30a60
DOI: 10.1145/2993318.2993351 - Freie Schlagwörter (EN)
- DevOps, continuous integration, RDF, data quality, quality monitoring, data integration, instant feedback
- Klassifikation (DDC)
- 000
- Publizierende Institution
- Universität Leipzig, Leipzig
- Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:15-qucosa2-159401
- Veröffentlichungsdatum Qucosa
- 01.08.2017
- Dokumenttyp
- Artikel
- Sprache des Dokumentes
- Englisch