Business Semantics Management: a Case Study for Competency-centric HRM

In this article we introduce a novel approach and tool for fact-oriented business semantics management that is inspired by agile design methods. We demonstrate and validate it in a realistic case study that was carried out within the European Codrive project. Codrive’s vision was to contribute to more meaningful competency-centric human resource management. Key challenges are the uniform publication of unambiguous competency information and “time-to-competency” agility. To this end, we developed a shared and formal knowledge representation of competency domains. Stakeholders include educational institutes, public employment organisations, and industry partners from different European countries. The resulting Vocational Competency Ontology wanted to provide a candidate best practice for engineering a community-shared and reusable semantic pattern base that can be applied by all stakeholders to semantically reconcile their contextualised competency models. 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

DOGMA-MESS: A Tool for Fact-Oriented Collaborative Ontology Evolution

Ontologies being shared formal specifications of a domain, are an important lever for developing meaningful internet systems. However, the problem is not in what ontologies are, but how they become operationally relevant and sustainable over longer periods of time. Fact-oriented and layered approaches such as DOGMA have been successful in facilitating domain experts in representing and understanding semantically stable ontologies, while emphasising reusability and scalability. DOGMA-MESS, extending DOGMA, is a collaborative ontology evolution methodology that supports stakeholders in iteratively interpreting and modeling their common ontologies in their own terminology and context, and feeding back these results to the owning community. In this paper we extend DOGMA Studio with a set of collaborative ontology evolution support modules.

De Leenheer, P. and Debruyne C. (2008) DOGMA-MESS: A Tool for Fact-Oriented Collaborative Ontology Evolution. In Proc. of On the Move to Meaningful Internet Systems 2008: ORM (ORM 2008) (Monterrey, Mexico), LNCS 5333, Springer, pp. 797-806

T-Lex: a Role-based Ontology Engineering Tool

Trog, D., Vereecken, J., Christiaens, S., De Leenheer, P., and Meersman, R. (2006) T-Lex: a Role-based Ontology Engineering Tool. In Proc. of the On The Move to Meaningful Internet Systems Workshops (OTM2006) (Montpelier, France) , LNCS 4278, Springer, pp. 1191-1200.

In the DOGMA ontology engineering approach ontology construction starts from a (possibly very large) uninterpreted base of elementary fact types called lexons that are mined from linguistic descriptions (be it from existing schemas, a text corpus or formulated by domain experts). An ontological commitment to such ”lexon base” means selecting/reusing from it a meaningful set of facts that approximates well the intended conceptualization, followed by the addition of a set of constraints, or rules, to this subset. The commitment process is inspired by the fact-based database modeling method NIAM/ORM2, which features a recently updated, extensive graphical support. However, for encouraging lexon reuse by ontology engineers a more scalable way of visually browsing a large Lexon Base is important. Existing techniques for similar semantic networks rather focus on graphical distance between concepts and not always consider the possibility that concepts might be (fact-) related to a large number of other concepts. In this paper we introduce an alternative approach to browsing large fact-based diagrams in general, which we apply to lexon base browsing and selecting for building ontological commitments in particular. We show that specific characteristics of DOGMA such as grouping by contexts and its ”double articulation principle”, viz. explicit separation between lexons and an application’s commitment to them can increase the scalability of this approach. We illustrate with a real-world case study.

In Collibra, the T-lex  plugin has been further extended in the Collibra Workbench to visualise business semantics engineering.

DOGMA-MESS: A Meaning Evolution Support System for Interorganizational Ontology Engineering

de Moor, A., De Leenheer, P., and Meersman, R. (2006) DOGMA-MESS: A Meaning Evolution Support System for Interorganizational Ontology Engineering . In Proc. of the 14th Int’l Conference on Conceptual Structures (ICCS 2006) (Aalborg, Denmark), LNAI 4068, Springer, pp. 189-203.

In this paper, we explore the process of interorganizational ontology engineering. Scalable ontology engineering is hard to do in interorganizational settings where there are many pre-existing organizational ontologies and rapidly changing collaborative requirements. A complex socio-technical process of ontology alignment and meaning negotiation is therefore required.   In particular, we are interested in how to increase the efficiency and relevance of this process using context dependencies between ontological elements. We describe the DOGMA-MESS methodology and system for scalable, community-grounded ontology engineering. We illustrate this methodology  with examples taken from a case of interorganizational competency ontology evolution in the vocational training domain.