Introduction to Semantic Technologies
This module is a gentle introduction to Semantic Technologies that provide easier ways to find, share, reuse and combine information. Semantic Technologies define and link data on the web or within an enterprise by developing languages to express rich, self-describing interrelations of data in a form that machines can process. They provide an abstraction layer above existing IT technologies that connects data, content and processes. Semantic Technology standards developed by W3C include
- a flexible data model RDF (Resource Description Framework) for storing data in graph databases;
- schema and ontology languages for describing concepts and relationships (RDFS and OWL);
- the query language SPARQL designed to query data across various systems and databases and to retrieve and process data stored in RDF format.
Applications of Semantic Technologies range from Linked Data, Wikidata, Healthcare and Pharma Industry, Supply Chain Management, Publishing and Media Management, Web Search and E-commerce to Data Integration in the Oil & Gas industry.
- to introduce the theoretical foundations of Semantic Technologies, including the languages RDF/S, SPARQL, the Web Ontology Language OWL;
- to provide the students with practical skills of modelling data using RDF/S, querying RDF triplestores, and building ontologies;
- to overview the current applications of Semantic Technologies in health care, media management, and industry;
- to demonstrate a few standard algorithms for classification of concepts in ontologies.
By the end of the module, the student should be able to:
1. understand fundamental concepts, advantages and limitations of Semantic Technologies;
2. understand and use the RDF framework and associated technologies such as RDFa and SPARQL;
3. understand and use the ontology language OWL 2 and its profiles;
4. understand the principles of ontology-based data access and integration;
5. understand the basics of knowledge representation with description logics.
1. Introduction to the module. Ontologies in (Computer) Science. Knowledge graphs. Schema.org. Wikidata. Lab: building a Don Corleone family ontology.
2. Is XML a semantic technology? The tree model of XML documents, XML Schema. Querying XML documents, XPath, JSON. Lab: building a pizza ontology.
3. Resource Description Framework (RDF). RDF Schema. RDF/S semantics. Terse RDF Triple Language Turtle. Linked Data. Lab: extracting RDF data from natural language texts.
4. SPARQL Query Language. Querying RDF triplestores. Lab: setting up and querying Apache Jena triplestore.
5. Ontology-based data access (OBDA). OBDA platform Ontop. Lab: setting up ontology-based access to the IMDB database.
6. Requirements for ontology languages. From RDFS to OWL. OWL ontologies.
7. Ontology engineering. OWL ontologies in life sciences and industry. Lab: designing a travel agent's ontology
8. Open vs closed worlds. Reasoning with OWL. Introduction to Description Logic and formal semantics.
By 2-hour written examination and by practical coursework. The written examination will have a weighting of 80% and the coursework a weighting of 20% of the final mark.
- G. Antoniou and F. van Harmelen. A Semantic Web Primer. MIT Press, 2004.
- P. Hitzler, M. Kroetzsch and S. Rudolph. Foundations of Semantic Web Technologies. Chapman & Hall, 2009.
- P. Szeredi, G. Lukacsy and T. Benko. The Semantic Web Explained. The technology and mathematics behind Web 3.0. Cambridge University Press, 2014.