Delivered at:: School of Data Analysis and Artificial Intelligence

Course type:: Elective course

When:: 4 year, 3 module

Instructors

Gerasimova, Olga

Zakharyaschev, Mikhail

Full Syllabus

Abstract

This course is an 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.

Learning Objectives

introduce the theoretical foundations of Semantic Technologies, including the languages RDF/S, SPARQL, the Web Ontology Language OWL
provide the students with practical skills of modelling data using RDF/S, querying RDF triplestores, relational databses and XML documents, building ontologies and using datalog
overview the current applications of Semantic Technologies in health care, media management, and industry;
demonstrate a few standard algorithms for classification of concepts in ontologies and answering queries

Expected Learning Outcomes

understand fundamental concepts, advantages and limitations of Semantic Technologies
understand and use deductive database systems
understand the basics of knowledge representation with description logics
understand the principles of ontology-based data access and integration
understand and use the RDF framework and associated technologies such as RDFa and SPARQL
understand and use the ontology language OWL 2 and its profiles
understand relational databases and XML documents

Course Contents

Introduction
Introduction to the module. Ontologies in (Computer) Science. Knowledge graphs. Schema.org. Wikidata. Seminar: building a Don Corleone family ontology.
XML/XML Schema, XPath
Is XML a semantic technology? The tree model of XML documents, XML Schema. Querying XML documents with XPath. JSON (JavaScript Object Notation). Seminar: Practical querying XML documents with XPath.
Querying relational databases
Querying relational databases: a quick survey. Seminar: Practical querying relational databases with PostgreSQL.
RDF/RDFs, language Turtle
Resource Description Framework (RDF). RDF Schema. RDF/S semantics. Terse RDF Triple Language Turtle. Seminar: producing RDF triples: by hand, from tables, from natural texts.
Query language SPARQL
RDF query Language SPARQL. Seminar: Querying RDF triplestores: DBpedia, German cities. Setting up and querying an Apache Fuseki triplestore.
Ontology-based data access
Introduction to ontology-based data access (OBDA). OBDA platform Ontop. Seminar: setting up ontology-based access to the IMDB database.
OWL, Ontology engineering
Requirements for ontology languages. From RDFS to OWL. OWL ontologies. Ontology. Ontology engineering. OWL ontologies in life sciences and industry. Seminar: designing an ontology using Protege.
Reasoning with OWL
Reasoning with OWL. Introduction to Description Logic and formal semantics. Seminar: answering queries with Protege.
Deductive databases
Deductive databases. Knowledge representation and query answering with datalog. Seminar: query answering with DLV and RDFox.

Assessment Elements

Exam
Written exam with discussion. Preparation time – 120 min. Students have to demonstrate knowledge of the material covered during the entire course and the ability to apply the materials. Технические требования: web-камера, микрофон, наушники / колонки
In-class tasks/ homeworks
The assessments consist of several in-class practical tasks.

Interim Assessment

Interim assessment (3 module)
0.4 * Exam + 0.6 * In-class tasks/ homeworks

Bibliography

Recommended Core Bibliography

Poli R., Healy M., Kameas A. (ed.). Theory and applications of ontology: Computer applications. – New York : Springer, 2010.

Recommended Additional Bibliography

Stuckenschmidt, H., Van Harmelen, F. Information sharing on the semantic web. – Springer Science & Business Media, 2005.

Bachelor’s Programme 'Applied Mathematics and Information Science'

Semantic Technologies