Semantic Reverse Engineering from Business Process Models


Business process modeling is becoming accepted to create innovative yet efficient enterprises and organizations. The support by various software tools allows both business and technical people to describe, design, model, build, execute, and monitor business processes on various levels of abstraction and according to different perspectives within one organization. Nevertheless, the management and the integration of different business processes across open systems might still be improved through the alignment with (i) ontologies [3] and (ii) the wider implementation of a service-oriented architecture.

The critical IT-Process divide (adopted from SUPER)

A conclusion from the European SUPER [i] project is that business process analysis techniques could benefit greatly from the use of semantic information. This is possible by annotating the elements that are relevant for analysis with ontological concepts. The benefits are two-fold: (1) the reuse of previous queries analysis can be promoted and (2) the proposed solutions reduce the gap that looms between information sharing among people (i.e. knowledge sharing) at the business/social level on the one hand; and information sharing between computer systems (i.e. data exchange) at the operational/technical level on the other hand [1].

The implementation of a service-oriented architecture to support business processes is the goal of two ongoing European research projects, i.e. PROLIX [ii] and TAS³ [iii]. The goal of PROLIX is to align learning with business processes to allow organizations to faster improve the competencies of their employees according to continuous changes in their business requirements. To reach this objective, PROLIX develops an open architecture for process-oriented learning and information exchange. The TAS³ project aims at having a European-wide impact on services dealing with personal information. More specifically, the project aims at securely accessing and processing information generated over a human lifetime stored in distributed business processes.

As part of these two ongoing European research projects, i.e. PROLIX and TAS³, we developed a conversion tool BPMOn that allows the semantic reverse engineering of business process models (BPMs) into DOGMA ontologies [4]. A DOGMA inspired ontology is based on the classical model-theoretic perspective and decomposes an ontology into a lexon base and a layer of ontological commitments. This is called the principle of double articulation [5]. By separating the elementary facts about a domain from the application specific constraints about these facts, DOGMA ontologies often capture more business rules and are more flexible than ontologies in other approaches. There is also support from an ontology evolution management framework [2].

DOGMA ontologies are based on NIAM [6] for database design and querying at the conceptual level. Although DOGMA ontologies can be easily understood by non-technical users, they are nevertheless logically well defined. During the presentation, we will describe the conversion process to convert a BPM, stored as an XPDL [iv] file, into a DOGMA ontology. We will also illustrate how the DOGMA approach can be used for business process modeling [7] and may facilitate the integration of different BPMs.

De Baer, P., De Leenheer, P., Zhao, G., and Meersman, R. (2009) Integrating Business Process Models with Ontologies. International Symposium on Service-Oriented Locally adapted Enterprise Architecture (Espoo, Finland)

References

[1] De Leenheer, P. and Van de Maele, F. (2009), The Semantic Wave: Messing Around or Hitting the Surf? Semantic Universe

[2] De Leenheer, P., Christiaens, S., and Meersman, R. (2009), Business Semantics Management: a Case Study for Competency-centric HRM. In Journal of Computers in Industry: Special Issue about Semantic Web Computing in Industry, Elsevier, forthcoming.

[3] De Leenheer, P. (2009) Ontology Elicitation. In Encyclopedia of Database Systems, eds. Liu, L. and Özsu, T., Springer, forthcoming

[4] Meersman, R., (2001), Ontologies and Databases: More than a Fleeting Resemblance, OES/SEO 2001 Rome Workshop.

[5] Spyns, P., Meersman, R., Jarrar, M. (2002) Data modelling versus ontology engineering. In SIGMOD Record 31(4), pages 12-17.

[6] G. Verheijen and J. Van Bekkum, (1982), NIAM, an information analysis method, Proceedings of the IFIP TC-8 Conference on Comparative Review of Information System Methodologies (CRIS 82), North-Holland, 1982.

[7] Zhao, G., Y. Gao , R. Meersman (2004), An Ontology-based approach to business modelling, Proceedings of the International Conference of Knowledge Engineering and Decision Support (ICKEDS2004), p.213-221.

i SUPER: Semantics Utilized for Process Management within and between Enterprises

ii PROLIX

iii TAS3: Trusted Architecture for Securely Shared Services

iv XPDL: XML Process Definition Language

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