Linked Computing and Data Systems (8ΚΠ02)
Instructor : Ioannis Anagnostopoulos
Assistant : Razis Gerasimos
Course typeCompulsory
Semester8
TermSpring Semester
ECTS5
Teaching hours3
Laboratory hours
Description
Introduction to the Semantic Web, Semantics and Knowledge Inference, Ontologies, Semantic Web Stack (XML, RDF, RDF Schema, OWL), queries in Semantic graphs, SPARQL. Tools for semantification and Ontology creation, Web 3.0 and semantic search. Open Data, Linked Open Data, and the LOD cloud. Big Data Analytics, Platforms and Big Data infrastructures (Amazon, GDFS/MapReduce, SPARK).
Course objectives

In this lesson, we present the basic technological stack related to the Semantic Web and Linked Data. It aims at describing the way the linked data (even in large scale) are modeled, and how machine-readable data from different sources can improve the quality of information and systems’ interoperability.

Textbooks/Bibliography
  • ΕΙΣΑΓΩΓΗ ΣΤΟ ΣΗΜΑΣΙΟΛΟΓΙΚΟ ΙΣΤΟ, GRIGORIS ANTONIOU, FRANK VAN HARMELEN
  • Το πλαίσιο της επιστήμης του Web, BERNERS-LEE, HALL, HENDLER, OHARA, SHADBOLT, WEITZNER
  • Συστήματα Παράλληλης Επεξεργασίας, Παπακωνσταντίνου Γεώργιος Κ.,Τσανάκας Παναγιώτης Δ.,Θεοχάρης Θ.
  • Semantic Web Programming, John Hebeler, Matthew Fisher, Ryan Blace, Andrew Perez-Lopez
  • Linked Data, David Wood, Marsha Zaidman, Luke Ruth, Michael Hausenblas
  • Big Data: Using Smart Big Data, Analytics and Metrics to Make Better Decisions and Improve Performance, Bernard B. Marr
Course material
http://eclass.uth.gr/eclass/