The exam is focused more on the theoretical aspects of the Semantic Web technologies, while the assignments have been dealing with practical use of the technologies.
The exam will be based on:
- The contents of the lectures
- See slides on the Lectures page
- G. Antoniou, P. Groth, F. van Harmelen, R. Hoekstra: A Semantic Web Primer. 3rd Edition. MIT Press, 2012.
- T. Heath, C. Bizer: Linked Data: Evolving the Web into a Global Data Space. Morgan & Claypool, 2011. http://linkeddatabook.com/editions/1.0/
The first book, A Semantic Web Primer, covers all the topics of the course, and the second one, Linked Data, provides a more practical view on the publishing methods and principles of publishing Linked Data (LD).
Regarding the books you should read at least:
- All the chapters of "A Semantic Web Primer"
- The chapters 1, 2, and 6 of "Linked Data"
In addition, you are encouraged to read the whole "Linked Data" book for deeper understanding of the LD field.
For our Finnish speaking students interested in learning semantic web and linked data technologies in Finnish, there is the following textbook available written by the lecturer of this course. This book is, however, not official course material since the course language is English:
Eero Hyvönen: Semanttinen web. Linkitetyn avoimen datana käsikirja. (Semantic Web. Handbook of Linked Open Data). Gaudeamus, 2018.
You are expected to have an understanding of the Semantic Web technology stack, its individual components, their roles and interplay in the "bigger picture", and a general idea what kind of applications can be built using this technology.
Key concepts of the course include:
- URI: global data resource identifiers on the web
- RDF: graph-based data model
- Correspondence to concrete serializations
- Benefits and use cases of different serialization formats (Turtle, RDF/XML, JSON-LD, RDFa, ...)
- Linked Data paradigm: web of data, "practical, simple Semantic Web"
- Publishing methods, principles, and best practices
- SPARQL: query language and protocol for RDF data
- Ontologies: modeling the domain and providing semantics
- Perspectives: philosophy, linguistics, terminology, computer science
- Languages: RDFS, OWL
- Semantics can be defined in terms of logical axioms or inference rules
- Different OWL syntaxes
- Different OWL versions (Full and DL) and profiles (EL, QL, RL)
- SKOS: language for lightweight ontologies
- Logical foundation of ontological reasoning: first order predicate logic, description logics
- Rule-based reasoning, based on Horn logic
- Different approaches: RIF, OWL RL, SWRL, SPIN
- Can be combined with description logics: Description Logic Programming (DLP)
- Unique Names Assumption (UNA) and Closed World Assumption (CWA)
- Monotonic and nonmonotonic reasoning
- Applications for Semantic Web and Linked Data
- Typical application areas and use cases
- Infrastructure for enabling the applications
The exam questions are typically short, focused questions with compact answers, rather than essays.
Some example exam question types:
- Technology/paradigm X (e.g., RDF, RDFS, OWL, SPARQL, RDFa, Linked Data, rule-based/monotonic/non-monotonic reasoning) or some part of it: why is it useful, what are the main benefits of it, what kind of applications it has?
- What are the core parts/characteristics of technology X?
- Compare technology/paradigm X to technology/paradigm Y: what are the differences, in what situations is X/Y useful? How are they used in Z? What new does Y bring to X?
- Given an example RDF serialization, what does it mean? E.g., what constraints does the given RDFS/OWL class description define to the class?
- Given an example RDF serialization, draw a corresponding RDF graph representation.
- Given an example RDF graph representation, write the corresponding RDF triples.
- Write a simple SPARQL query for selecting X from given example RDF data.
- What do the following RDF(S)/OWL/SPARQL concepts/structures mean: X, Y, Z?