Traditionally listed as a part of the major branch of philosophy known as metaphysics, ontology is a data model knowledge as a set of concepts within a domain, and how such entities can be grouped, related within a hierarchy, and subdivided according to similarities and differences.
Creation of semantic ontology consists of five parts:
- Organizing and Scoping. The organizing and scoping activity establishes the purpose, viewpoint, and context for the ontology development project, and assigns roles to the team members.
- Data Collection. During data collection, raw data needed for ontology development is acquired.
- Data Analysis. Data analysis involves analyzing the data to facilitate ontology extraction.
- Initial Ontology Development. The intitial ontology development activity develops a preliminary ontology from the data gathered. expressions.
- Ontology Refinement and Validation. The ontology is refined and validated the ontology to complete the development process.
This process is used in creating a working model for information relevant to a particular domain or area of interest.
Ontologies provide a common vocabulary for use by independently developed resources, processes, services. Ontologies allow organizations sharing common services to agree with regard to the usage and unambiguous meaning of the things comprising those services. Ontologies are superb tools for content management for long-term retention and re-use. They enable software systems and to make inferences about data and come to relevant conclusions with regard to them, to search and retrieve disparate data over diverse sources, to perform on-the-fly association of information to suit particular, ad hoc purposes and queries – providing answers to questions rather than just ‘hits’ to searches
Developing an ontology is a rigorous and ongoing process. When finished, the ontology must guide a reasoning process in a way that is applicable to individuals in the domain, adequate to interpreting any individual in the domain, consistent among its axioms and coherent and interdependent among its concepts.
Creating an ontology requires iterative explication and conceptualization, working closely with domain experts to articulate essential concepts that, until now, may have been only tacit parts of their expertise. Key system stakeholders, owners and resources for instance knowledge are identified.
The careful articulation of business functions and processes in terms of actors and system interactions – are vital to providing context, focus and project closure. We identify anticipated re-use and evolution pathways, as well as any critical standards and resources the system must interoperate with.
The ontologist and the domain expert to visualize and critique the model as it grows over time. The conceptual model simplifies technical and formal aspects of the ontology, and helps us to articulate architectural trade-offs, costs and benefits as well as elicit the kinds of questions that need to be answered by the ontology.
Thematix uses canonical ontological definitions, rather than re-invent them. Thus, namespace definitions, related metadata, units, measurements, standards, governance policies and other commonly used structures & vocabularies are imported and used as part of the ontology to the degree appropriate and practicable.
Thematix adheres to the principles of ontological analysis stated in IDEF5, which “provides a theoretically and empirically well-grounded method specifically designed to assist in creating, modifying, and maintaining ontologies,” and which when used leads to higher quality and lower costs.