Peter De Baer

On Constructing, Grouping and Using Topical Ontology for Semantic Matching

An ontology topic is used to group concepts from different contexts (or even from different domain ontologies). This paper presents a pattern-driven modeling methodology for constructing and grouping topics in an ontology (PAD-ON methodology), which is used for matching similarities between competences in the human resource management (HRM) domain. The methodology is supported by a tool called PAD-ON. This paper demonstrates our recent achievement in the work from the EC Prolix project. The paper approach is applied to the training processes at British Telecom as the test bed.

Towards a Pattern-Driven Topical Ontology Modeling Methodology in Elderly Care Homes

This paper presents a pattern-driven ontology modeling methodology, which is used to create topical ontologies in the human resource management (HRM) domain. An ontology topic is used to group concepts from different contexts (or even from different domain ontologies). We use the Organization for Economic Co-operation and Development (OECD) and the National Vocational Qualification (NVQ) as the resource to create the topical ontologies in this paper. The methodology is implemented in a tool called PAD-ON suit. The paper approach is illustrated with a use case from elderly care homes in UK.

Facilitating ontology (re)use by means of a categorization framework

Ontologies as means for conceptualizing and structuring domain knowledge within a community of interest are seen as a key to realize the Semantic Web vision However, the decentralized nature of the Web makes achieving consensus across communities difficult, thus, hampering efficient knowledge sharing between them To address this problem of heterogeneity we propose a Categorization Framework (CF) that makes it possible to use (multilingual) terminology to specify concepts and concept relations in domain ontologies Such CF could describe the meaning of concepts and concept relations by means of terminological information and external references We believe that such (multilingual) ontology description could enhance the (re)usability and facilitate the coordination of domain ontologies.

Termontography and DOGMA for Knowledge Engineering within PROLIX

In this article, we describe our ongoing research to combine two approaches, i.e. Termontography and DOGMA, for knowledge engineering. Both approaches have in common that they mainly rely on natural language to describe meaning. Termontography is a special form of terminography that results in an ontologically structured terminological resource. DOGMA is an abbreviation of Developing Ontology Guided Mediation for Agents. The DOGMA approach results in a scalable and modular ontology that can easily be (re)used for different domains and applications. Both Termontography and DOGMA have already been used separately during several research projects. In this article we explain how both approaches are being combined within the PROLIX project, and what the advantages of this combination are. The goal of PROLIX is to develop an open, integrated reference architecture for process-oriented learning and information exchange.

An Evolutionary Ontology Approach for Community-Based Competency Management

In this article we describe an evolutionary ontology approach that distinguishes between major ontology changes and minor ontology changes. We divide the community in three (possibly overlapping) groups, i.e. facilitators, contributors, and users. Facilitators are a selected group of domain experts who represent the intended community. These facilitators define the intended goals of the ontology and will be responsible for major ontology and ontology platform changes. A larger group of contributors consists of all participating domain experts. The contributors will carry out minor ontology changes, like instantiation of concepts and description of concept instances. Users of the ontology may explore the ontology content via the ontology platform and/or make use of the published ontology content in XML or HTML format. The approach makes use of goal and group specific user interfaces to guide the ontology evolution process. For the minor ontology changes, the approach relies on the wisdom of crowds.