CSCI8380 - Fall 2008
Advanced Topics in Information Systems
Instructor: Prof. I. Budak Arpinar (www.cs.uga.edu/~budak)
· familiarity with the World Wide Web
· basic Java programming skills and database background
· A Semantic Web Primer by Grigoris Antoniou, and Frank van Harmelen, MIT Press, Cambridge, MA, 2004.
· Semantic Web Technologies: Trends and Research in Ontology-based Systems by John Davies (Editor), Rudi Studer (Co-Editor), Paul Warren (Co-Editor), John Wiley & Sons, July 2006.
· Building an Intelligent Web by R. Akerar, and P. Lingras, Jones and Bartlett Publishers, 2008.
· Towards the Semantic Web by J. Davies, D. Fensel, and F. van Harmelen, Wiley 2005.
· Spinning the Semantic Web by D. Fiensel, J. Hendler, H. Lieberman, and W. Wahlster, The MIT Press, 2003.
· Service-Oriented Computing by M. Singh, and M Huhns, Wiley, 2005.
In this course you will learn what the Semantic Web is, and what its advocates believe it will eventually be able to do. You will be introduced to many useful Semantic Web languages and tools. In addition, other Semantic Web related topics such as web services, peer-to-peer systems and social networking will be discussed.
Subjects will be introduced by the instructor and by the students in their presentations to the class.
Course Web Page: http://www.cs.uga.edu/~budak/atis_f08.html (under preparation)
TOPICAL OUTLINE (subject to minor change)
· Semantic Web
§ Ontology design & development
§ Web ontology standards RDF(S) & OWL
§ Ontology quality
§ Meta-data extraction & document annotation
§ Semantic similarity
§ Semantic associations (SemDis)
§ Semantic search
§ Storing & querying ontologies (SPARQL)
§ NLP and semantic web
· Web Services (WS)
§ WS description and discovery
§ WS composition
§ Semantic WS (METEOR-S)
§ Transactional WS
§ Quality-driven WS
· Peer-to-Peer (P2P) systems
§ Emergent semantics
§ Searching P2P networks
§ Semantic P2P networks
· New database trends
§ Social networks (trust and reputation management, FOAF)
§ Web-based data integration and interoperability
§ Personal data management
GRADING POLICY (subject to minor change)
1. Term project – groups of 2 (40%)
2. Individual project assignments (%20)
3. Research paper reviews/presentations (20%)
4. Class participation (%5)
5. Exam(s) (15%)