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Course Catalog 2013-2014
MAT-82106 Semantic Modelling, 4 cr |
Additional information
Lectured every second calendar year (during academic years starting with an odd number). Implementation announcements and news are available at the teaching home page of the TUT Department of Mathematics, Intelligent Information Systems Laboratory.
Suitable for postgraduate studies
Person responsible
Ossi Nykänen
Lessons
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Learning Outcomes
Semantic modelling is about capturing discrete or conceptual domain information using generic modelling primitives. This enables analysing, integrating, and searching knowledge, and deducing implicit information within specific domain(s) of interest. In this course, we familiarize ourselves with the basic concepts, techniques, and applications related to semantic modelling. The methodological foundation for the course is established by logic programming and description logic(s). We apply these methods in the context of Semantic Web technologies; in (ontology) modelling and query applications. The main objectives of the course are to understand the role of logical descriptions in knowledge-intensive applications, and to get hands-on experience on implementing simple applications.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Methodological foundation: Basic (discrete mathematics) semantic modelling strategies; Predicate calculus as reasoning and representation system; Management and complexity issues; Description Logic(s). | Prolog. | |
| 2. | Technological foundation: (W3C Semantic Web) Resource Description Framework (RDF, RDF Schema); Simple Knowledge Organization System (SKOS) SPARQL query language; Web Ontology Language (OWL). | Technological context; Serialization syntaxes; Related applications. | |
| 3. | Application development: Linked Data; Domain ontology/rule modelling; Semantic Web Programming. | Related frameworks (Jena) and integrated development environments (Eclipse, Protege); Microformats. |
Instructions for students on how to achieve the learning outcomes
The grade is based on the assignments and the final exam.
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Prerequisite relations (Requires logging in to POP)
Correspondence of content
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More precise information per implementation
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