Umeå universitets logga

umu.sePublikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Extracting event data from document-driven enterprise systems
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Free University of Bozen-Bolzano, Bolzano, Italy.ORCID-id: 0000-0001-5174-9693
Hasselt University, Hasselt, Belgium; Maastricht University, MD, Maastricht, Netherlands.
Virtual Vehicle Research GmbH, Graz, Austria.
Free University of Bozen-Bolzano, Bolzano, Italy.
2023 (Engelska)Ingår i: Advanced information systems engineering: 35th International conference, CAiSE 2023, Zaragoza, Spain, June 12–16, 2023, proceedings / [ed] Marta Indulska; Iris Reinhartz-Berger; Carlos Cetina; Oscar Pastor, Springer, 2023, s. 193-209Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

The preparation of input event data is one of the most critical phases in process mining projects. Different frameworks have been developed to offer methodologies and/or supporting toolkits for data preparation. One of these frameworks, called OnProm, relies on sophisticated semantic technologies to extract event logs from relational databases. The toolkit consists of a series of general steps, meant to work on arbitrary, legacy databases. However, in many settings, the input database is not a legacy one but is structured with conceptually understandable object types and relationships that can be effectively employed to support business users in the extraction process. This is, for example, the case for document-driven enterprise systems. In this paper, we focus on this class of systems and propose a guided approach, erprep, to support a group of business and technical users in setting up OnProm with minimal effort. We demonstrate the approach in a real-life use case.

Ort, förlag, år, upplaga, sidor
Springer, 2023. s. 193-209
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 13901
Nyckelord [en]
Data preparation, ERP systems, event log extraction, Ontology-based event modeling
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:umu:diva-212113DOI: 10.1007/978-3-031-34560-9_12ISI: 001284775300012Scopus ID: 2-s2.0-85163937628ISBN: 978-3-031-34559-3 (tryckt)ISBN: 978-3-031-34560-9 (digital)OAI: oai:DiVA.org:umu-212113DiVA, id: diva2:1782756
Konferens
35th International Conference on Advanced Information Systems Engineering, CAiSE 2023, Zaragoza, Spain, June 12–16, 2023
Tillgänglig från: 2023-07-17 Skapad: 2023-07-17 Senast uppdaterad: 2025-04-24Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextScopus

Person

Calvanese, Diego

Sök vidare i DiVA

Av författaren/redaktören
Calvanese, Diego
Av organisationen
Institutionen för datavetenskap
Datavetenskap (datalogi)

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetricpoäng

doi
isbn
urn-nbn
Totalt: 123 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf