The Open UniversitySkip to content

SENTINEL: a semantic business process monitoring tool

Pedrinaci, Carlos; Lambert, David; Wetzstein, Branimir; van Lessen, Tammo; Cekov, Luchesar and Dimitrov, Marin (2008). SENTINEL: a semantic business process monitoring tool. In: The First International Workshop on Ontology-supported Business Intelligence (OBI2008), 26-30 Oct 2008, Karlsruhe, Germany.

Full text available as:
PDF (Accepted Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB)
DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


Business Activity Monitoring (BAM) aims to support the real-time analysis of business processes in order to improve the speed and effectiveness of business operations. Providing a timely, integrated high-level view on the evolution and well-being of business activities within enterprises constitutes a highly valuable analytical tool for monitoring, managing and hopefully enhancing businesses. However, the degree of automation currently achieved cannot support the level of reactivity and adaptation demanded by businesses. We argue that the fundamental problem is that moving between the business level and the IT level is insufficiently automated and suggest an extensive use of semantic technologies as a solution. In particular, we present SENTINEL a Semantic Business Process Monitoring tool that advances the state of the art in BAM by making extensive use of semantic technologies in order to support the integration and derivation of business level knowledge out of low-level audit trails generated by IT systems.

Item Type: Conference or Workshop Item
Copyright Holders: 2008 ACM
Extra Information: OBI '08 Proceedings of the first international workshop on Ontology-supported business intelligence
ISBN: 978-1-60558-219-1
Keywords: business activity monitoring; business process analysis; semantic business process management
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 23360
Depositing User: Kay Dave
Date Deposited: 18 Nov 2010 10:28
Last Modified: 12 Dec 2018 22:38
Share this page:


Altmetrics from Altmetric

Citations from Dimensions

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU