Community-driven Evolution of Knowledge-intensive Systems


De Leenheer, P. and Meersman, R. (2007) Towards Community-driven Evolution of Knowledge-intensive Systems. In Proc. of the 6th Int’l Conf. on Ontologies, DataBases, and Applications of Semantics (ODBASE 2007) (Vilamoura, Portugal), LNCS, Springer

Co-evolution in a knowledge-intensive community

Co-evolution in a knowledge-intensive community

This article wants to address the need for a research effort and framework that studies and embraces the novel, difficult but crucial issues of adaptation of knowledge resources to their respective user communities, and \emph{vice versa}, as a fundamental property within knowledge-intensive internet systems. Through a deep understanding of real-time community-driven evolution of so-called ontologies, a knowledge-intensive system can be made operationally relevant and sustainable over longer periods of time. To bootstrap our framework, we adopt and extend the DOGMA ontology framework, and its community-grounded ontology engineering methodology DOGMA-MESS, with an ontology that models community concepts such as business rules, norms, policies, and goals as first-class citizens of the ontology evolution process. Doing so ontology evolution can be tailored to the needs of a particular community. Finally, we illustrate with an example from an actual real-world problem setting, viz. interorganisational exchange of HR-related knowledge.

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