Damien Trog

T-Lex: a role-based ontology engineering tool

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 applications commitment to them can increase the scalability of this approach We illustrate with a real-world case study.

Towards ontological commitments with Ω-RIDL markup language

In the DOGMA (Developing Ontology-Grounded Methods and Applications) ontology engineering approach, ontology construction starts from an uninterpreted base of elementary fact types, called lexons, which are mined from linguistic descriptions. Applications that ontologically commit to such a lexon base are assigned a formal semantics by mapping the application symbols to paths in this lexon base. Besides specifying which concepts are used, we restrict how they may be used and queried with semantic constraints, or rules, based on the fact-based database modeling method NIAM/ORM. Such ontological commitments are specified in the Ω-RIDL1 language. In this paper we present the Ω -RIDL Markup Language and illustrate with a case from the field of Human Resources Management.

Mapping OWL-DL into ORM/RIDL

In this paper, we analyze the semantics of OWL-DL and ORM, and explain how to represent OWL-DL constructs in ORM without losing semantics. We demonstrate this in a formal manner as much as possible. We show it is possible to convert most constructs, except for what are called property restrictions, and discuss the implications.

Toward a Community Vision Driven Topical Ontology in Human Resource Management

Todays industries require ontology engineering to be more community vision driven and ontological resources have more dimensions. This paper shows our achieved goals in the EU Prolix project. Firstly, we analyze the user requirements, including tuning Business Process Modelling efforts into ontology engineering tasks. Secondly, we design a scalable and community driven architecture for ontology development. Then, feasible ontology models are created. The task of creating ontology models depends heavily on conceptual architecture of ontology based competence analysis. We illustrate with the requirement analysis from BT (British Telecom).

Methodological Approach to Determine Appropriately Annotated Resources in Narrow Folksonomies

Folksonomies are community managed vocabularies, and do not limit end users to employ a strict terminology in their annotating activities. Users are free to create and use whatever tag they like. Folksonomies have also been criticized to produce low quality meta data due to reduced quality control. In the case of narrow folksonomies where resources are evaluated by only one person there is no certainty that the resources are appropriately annotated. In this paper, we suggest a three-phase iterative approach to determine the properties, expressed in terms of tag ambiguity, of resources appropriately annotated in a narrow folksonomy to improve information retrieval. We also show brief results of the first steps of that approach in a case study involving a narrow folksonomy.

Model Ontological Commitments Using ORM + in T-Lex

When designing and developing ontology based applications, we semantically ground them by ontologically committing the application rules to their respective domain. These rules can be, for instance decision rules for a decision support system. For the DOGMA framework we have introduced ORM + , a novel extension of ORM for modeling, visualizing and interchanging ontological commitments. In this paper, we illustrate our ongoing research on ORM + and T-Lex as its supporting tool. We demonstrate in the field of on-line customer management.