
PhD Student
Department of Information Systems
The University of Melbourne
Room 2.34, ICT Building, 111 Barry St, Carlton, VIC, AustraliaPhone: +61 3 8344 1555
Email: d.klesspgrad.unimelb.edu.au
Jump down this page to: Research Interests : Thesis : Publications : Background : Awards
Ontologies, Vocabularies, Knowledge Organization Systems (KOS), Information Organization, Metamodeling, Datamodeling, Domain modeling, Knowledge representation, Library and Information Studies, Information Science
Content Management, Information Management, Knowledge Management (KM), Model-driven architecture (MDA), Information Architecture (AI), Computer Science (CS), Information Systems (IS), Artificial Intelligence (AI), Semantic Web, Information retrieval, Indexing, Tagging, Metadata
Framework for the description and comparison of semantic models
Exploring models, meta-languages or similar instruments that make characteristics of existing types of semantic models understandable and comparable.
Semantic models as they are typically produced in various communities:
- (Formal) ontologies from the Artificial Intelligence (AI), Computer Science (CS), and the Semantic Web community
- Conceptual (data) models from the Information Systems (IS) community
- Vocabularies / Knowledge Organization Systems (KOS) from the Library and Information Studies (LIS) community
- Any other types of domain descriptions for the organization, representation and retrieval of information and knowledge
More specifically, the analysis shall encompass at least the first two, but possibly also further types of semantic models in the following priority list:
- Thesauri
- Web-Ontologies (generally published in OWL)
- Class Diagrams
- Semantic models applied in industrial organization
- Ontologies (logic-based such KIF, Description Logic / DL or Common Logic / CL)
- Classification Schemes
Further candidates of future analysis include:
Synonym rings, Subject headings, Name authority lists, Semantic Networks, Taxonomies, Folksonomies, Topic maps, Directory structures, Navigation bars, Table of contents, Indexes, Terminologies, Lexicons, Dictionaries, Glossaries
A framework, i.e. a set of models, meta-languages or similar instruments revealing characteristics of semantic models:
- Data-models / meta-models: revealing their conceptual nature
- Properties such as the 'specificity' or 'complexity': revealing the qualityin which a specific domain is described
- Use cases: revealing the context in which they are typically applied
Moreover, a meta-language / reference language shall a) express and systemize theconceptual elements that can be found across the various types of semantic models and b) translate between the different terminologies in the various communities
The combination of:
- Understandability, i.e. comprehensibility by all of the various communities that produce semantic models as well as business analysts, information architects or other practitioners planning and designing semantic models.
- Consistency, i.e. the applicability of the framework to describe / specify each type of semantic models in the same way.
- Expressivity, i.e. the instrument should be able to reveal all the important characteristics of semantic models, their differences and commonalities
The research is planned to iterate between analysing specific types of semantic models, building/synthesizing the framework and applying it.
- More qualified strategic decisions for or against a type of semantic model
- Better evaluation of semantic models
- Improved interoperability analysis for the various types of semantic models
- Better understandability of semantic modeling as a subject field
- Facilitated learning across the communities producing semantic models
Please download the prelimiary draft version of my PhD confirmation report and its presentation for a more complete description of my research.