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Semantic Enhancement: Key to Massive and Heterogeneous Data Pools

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. Outline. Introduction

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Semantic Enhancement: Key to Massive and Heterogeneous Data Pools

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  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/ • LMF: http://semanticweb.org/wiki/LinkedMediaFrameworkhttp://code.google.com/p/kiwi/

  14. Thank you for your attention

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