• Peter Mika, Yahoo! Research, Barcelona, Spain
  • Elena Simperl, Karlsruhe Institute of Technology, Germany

Track Program Committee

  • Harith Alani, Knowledge Media Institute, OU, UK
  • Sören Auer, Universität Leipzig, Germany
  • Chris Bizer, University of Mannheim, Germany
  • Oscar Corcho, UPM, Spain
  • Mariano Consens, University of Toronto, Canada
  • Gianluca Correndo, University of Southampton, UK
  • Richard Cyganiak, NUIG, Ireland
  • Ying Ding, Indiana University, USA
  • John Domingue, Knowledge Media Institute, OU, UK
  • Fabien Gandon, INRIA, France
  • Birte Glimm, University of Ulm
  • Tudor Groza, University of Queensland, Australia
  • Michael Hausenblas, NUIG, Ireland
  • Tom Heath, Talis, UK
  • Pascal Hitzler, Kno.e.sis, Wright State University, USA
  • Aidan Hogan, NUIG, Ireland
  • Spyrous Kotoulas, IBM, Ireland
  • Craig Knoblock, USC, USA
  • Jens Lehmann, Universität Leipzig, Germany
  • Vanessa Lopez, IBM, Ireland
  • Pablo Mendes, Open Knowledge Foundation, Germany
  • Natasha Noy, SMI, Stanford University, USA
  • Alexandre Passant,, Ireland
  • Heiko Paulheim, Technische Universität Darmstadt, Germany
  • Matthew Rowe, University of Lancaster, UK
  • Manuel Salvadores, SMI, Standord University, USA
  • Aanod Sane, Yahoo, USA
  • Amit Sheth, Kno.e.sis, Wright State University, USA
  • Milan Stankovic, Hypios, France
  • Hideaki Takeda, National Institute of Informatics, Japan
  • Jamie Taylor, Google, USA
  • Nicolas Torzec, Yahoo! Labs, USA
  • Jacco van Ossenbruggen, Centrum voor Wiskunde en Informatica, The Netherlands
  • Denny Vrandecic, Wikimedia, Germany


Linking data - and not just conventional Web documents - is one of the core building blocks of the Semantic Web. As semantic standards and technologies become mainstream - most prominently through developments such as Google's Knowledge Graph, Facebook's Open Graph Protocol, the initiative, and the Linked Open Data Cloud community movement - we experience a rapid growth in the amount, quality, and variety of usage scenarios for linked data sets. More and more organizations in the public and private domains are not just publishing their data according to Linked Data principles, but use the resulting Web-wide wealth of resources, rich in meaning and structure, to expand the functionality of their information-intensive applications.

The track focuses on research addressing challenges and opportunities associated with realizing and using Web-scale, distributed semantic data graphs, covering all aspects of the linked data management life cycle, including the creation of new linked Data, interlinking, entity extraction, enrichment of traditional Web content with semantic annotations, combinations of linked and other types of data, quality analysis, evolution and dynamics, and consumption through query processing and mining.

Topics of interest

Topics of interest include, but are not limited to
  • Publication of linked data
  • Data set dynamics and evolution
  • Data interlinking
  • Data set curation
  • Semantic annotation and markup
  • Algorithms for linking textual and data sources and entities
  • Semantic social network representation and analysis
  • Automatic and socially inspired algorithms for linked data management
  • Scalability of graph-based algorithms and infrastructures
  • Data mining for linked data
  • User interfaces and user/social interactions for linked data
  • Provenance, privacy, and rights management for linked data