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Journal of Zhejiang University SCIENCE C 2012 Vol.13 No.4 P.308-310

http://doi.org/10.1631/jzus.C1101011


Enterprise applications of semantic technologies for business process management


Author(s):  Ralf Mueller

Affiliation(s):  Oracle BPM Product Development, Redwood City, CA, USA

Corresponding email(s):   ralf.mueller@oracle.com

Key Words:  No Keyword


Ralf Mueller. Enterprise applications of semantic technologies for business process management[J]. Journal of Zhejiang University Science C, 2012, 13(4): 308-310.

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Abstract: 
We would like to give a short perspective on how BPM can benefit from the technical advances in semantic technologies over the last 10 years. BPM spans a wide range of concepts, technologies, and personas. From a top-down perspective, a BPM project typically starts with the definition of the company value chains, the strategies and goals that should be achieved, and the key performance indicators (KPIs) that are used to measure the success or failure of well-defined objectives. The value chains are further decomposed into supporting business processes (typically modeled in BPMN 2.0 (Silver, 2009)), applications, and services. An implementation of those artifacts is then performed using the tenets of a Service-Oriented Architecture (SOA). We are considering the use of semantic technologies invaluable in formalizing the complex relationships between the involved entities of a BPM system and providing a unified method for query and business rules. Understanding the exact semantics of a BPM system will foster agility and reduce proliferation of services and processes in an enterprise.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Allemang, D., Hendler, J., 2011. Semantic Web for the Working Ontologist (2nd Ed.). Morgan Kaufmann.

[2]Antoniou, G., van Harmelen, F., 2004. A Semantic Web Primer. MIT Press.

[3]Fensel, D., 2001. Ontologies: a Silver Bullet for Knowledge Management and Electronic Commerce. Springer.

[4]Silver, B., 2009. BPMN Method & Style. Cody-Cassidy Press.

[5]Wood, D., 2010. Linking Enterprise Data. Springer.

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