1. Semantic Enhancement: Key to Massive and Heterogeneous Data Pools Violeta Damjanovic, Thomas Kurz, Rupert Westenthaler, Wernher Behrendt, Andreas Gruber, Sebastian Schaffert Salzburg Research September 19-22, 2011 ERK 2011, Portoroz, Slovenia

2. Outline Introduction Background: Semantic Enhancement Approaches and Techniques Experiences: Semantic Enhancement via Apache Stanbol and LMF (Linked Media Framework) Further Integration Conclusion

3. Background: Semantic Enhancement Approaches and Techniques SW: „a dream for the Web [in which computers] become capable of analysing all the data on the Web – the content, links, and transactions between people and computers“ (1999, T.B. Lee & M. Fischetti) SW standards and directions – RDF: a framework for presenting information on the Web – OWL: a language designed for apps that need to process the content of information – LOD: a way to bootstrap the SW by publishing and interconnecting datasets using RDF

4. Background: Semantic Enhancement Approaches and Techniques Semantic search and browsing Semantic mediation: merging and mapping Semantic annotation Semantic analytics and knowledge discovery

5. Background: Semantic Enhancement Approaches and Techniques Semantic search and browsing – Augmenting traditional keyword search with SW technologies – Basic concept location (e.g. multi-faceted search, sematic auto-completion, search behavior research...) – Complex constraint queries for creating query patterns as intuitively as possible – Problem solving – Connecting path discovery

6. Background: Semantic Enhancement Approaches and Techniques Semantic mediation: merging and mapping – Merging: unifies two or more ontologies with overlapping parts into a single ontology that includes all information from the sources – Mapping: builds the mapping statement that define relationships between concepts of ontologies and rules that specify transformation between two ontologies

7. Background: Semantic Enhancement Approaches and Techniques Semantic annotation – General frameworks: W3C Annotea, CREAM Semantic analytics and knowledge discovery – Processing of queries on LOD Federated and centralized approaches Link traversal-based query execution Query federation

8. Experiences: Semantic Enhancement via Apache Stanbol and LMF Apache Stanbol (FP7 IP IKS project)

9. Experiences: Semantic Enhancement via Apache Stanbol and LMF LMF (Linked Media Framework)

10. Linked Media Principles LMF implements the following extensions to Linked Data: – it extends the Linked Data principles with RESTful principles for addition, modification, and deletion of resources – it extends the Linked Data principles by means to manage content and meta-data alike resources using MIME to URL mapping

11. LMF Service-oriented Architecture LMF Core (implements extensions to Linked Data) – Linked Data Server – LMF SPARQL endpoint (querying the data within the LMF) LMF Semantic Search (search based on Apache SOLR) LMF Linked Data Cache (implements a cache to the LOD Cloud that is used when querying the content of the LMF) LMF Reasoner (a rule-based reasoner) LMF Permissions LMF Enhancer LMF Media Interlinking LMF Versioning

12. Further Integration LMF Enhancer component Stanbol Enhancer LMF Reasoner Stanbol Reasoner

13. Conclusion Apache Stanbol: http://incubator.apache.org/stanbol/ http://incubator.apache.org/stanbol/ LMF: http://semanticweb.org/wiki/LinkedMediaFra mework http://code.google.com/p/kiwi/ http://semanticweb.org/wiki/LinkedMediaFra meworkhttp://code.google.com/p/kiwi/

14. Thank you for your attention