Information Architecture and Semantic Technologies 6 Credits

Course Contents

The course details the role of information architecture as a meaning-making structure, and it provides a framing for the systemic design of information products for digital environments. The experience of information navigation should be coherent for different applications and systems. The course explains details methods and techniques for modelling and structuring information. Standard vocabularies, schemas, and data sources are described, including FOAF, SIOC, SKOS, and DBpedia. When creating an information place, it can be advantageous to link to datasets available on the web. Linked data is introduced as a means to enrich the information architecture of a digital product. This allows for richer semantic description to be included in an application and used in a machine-processable way. The course describes semantic modelling with RDF(S), querying RDF datasets with SPARQL, and embedding snippets of semantic data into HTML pages with RDFa. The evolving semantic web and OWL ontologies are introduced as well.
When semantics is attached to information, it becomes knowledge resulting in the potential to generate actions. Knowledge modelling is the next step in providing more intelligent and smart applications, e.g. being able to adapt, gather information from other sources and give recommendations. To this end, semantic technologies are introduced for knowledge modelling and sharing.
The topics covered in the course include:
- information needs, information modelling and structuring
- content categorization, tagging, and metadata thesauri, and vocabularies
- tagging and metadata
- information navigation system, search systems, and content indexing
- concepts, semantic relationships and conceptual modelling ontologies
- information navigation system, search systems and content indexing
- conceptual modelling and knowledge modelling
- semantic technologies for knowledge modelling, including XML, RDF(S), SPARQL, OWL
- knowledge and information sharing, and linking open data
- standard vocabularies, schemas, and linking open data
- modelling data with RDF(S)
- XML, HTML and RDFa tags
- querying RDF datasets with SPARQL
- the evolving semantic web and OWL ontologies

Prerequisites

Passed courses at least 90 credits within the major subject in Computer Engineering, Electrical Engineering (with relevant courses in Computer Engineering), Informatics, Computer Science, Interaction Design (with relevant courses in web programming), and completed course User Experience Design, 6 credits. Proof of English proficiency is required.

Level of Education: Master
Course code/Ladok code: TSTS26
The course is conducted at: School of Engineering Last modified 2024-03-08 11:25:21