DynamOnt – Methodology for Dynamic Ontology Creation
Collaborative development and semantic enrichment of knowledge models
Collaboration of distributed knowledge communities is a rapidly increasing application field, e.g. in international enterprises, scientific research teams, e-learning communities. For efficient collaboration the common understanding of information is a decisive factor. A systematic approach to gain this common understanding is the dynamic creation ontologies, leading to a more efficient use of shared information resources. At present, the creation of high-quality ontologies is a very time consuming and expensive task. Therefore, such ontologies are available only for few thematic field, where there is hope for significant economies of scale, e.g. the health sector, in tourism and in the insurance sector. What is still missing is a methodology supported by tools, which would enable domain experts (who are not ontology building experts) to create ontologies on the fly, yet based on sound principles, created in short time. “Dynamic” means that these ontologies can then be extended and refined over time, possibly by other non-IT experts, can evolve to become more axiomatised, and can be personalised and localised by individuals and groups without losing touch with the community’s preferred interpretation. At present, none of the above requirements are sufficiently supported by methodologies and tools. This leads to many poorly analysed “ontologies” being published on the Web. This is likely to become a trust problem and an economic hurdle for the “semantic” Web.
The DynamOnt project will:
- develop a methodological framework for dynamic generation and maintenance of ontologies
- support and enhance the methodology with findings from the research field of formal ontology
- develop process models that enable user communities to personalise ontologies with common conceptual workspaces
- align the work done in ontologies and object oriented modelling with related work in terminology and lexical semantics in order to adequately reflect semantic richness and complexity of knowledge resources
- evaluate and validate the methodological framework in three environments
