Methods and Tools for Ontology Building, Learning and Integration – Application in the SYNAT Project

One of the main goals of the SYNAT project is to equip scientific community with a knowledge-based infrastructure providing fast access to relevant scientific information. We have started building an experimental platform where different kinds of stored knowledge will be modeled with the use of ontologies, e.g. reference/system ontology, domain ontologies and auxiliary knowledge including lexical language ontology layers. In our platform we use system ontology defining “system domain” (a kind of meta knowledge) for the scientific community, covering concepts and activities related to the scientific life and domain ontologies dedicated to specific areas of science. Moreover the platform is supposed to include a wide range of tools for building and maintenance of ontologies throughout their life cycle as well as interoperation among the different introduced ontologies.

The paper makes a contribution to understanding semantically modeled knowledge and its incorporation into the SYNAT project. We present a review of ontology building, learning, and integration methods and their potential application in the project.