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Linked AI: AAAI Spring Symposium "Linked Data Meets Artificial Intelligence", March 22-24 2010

AAAI Spring Symposium on Linked Data Meets Artificial Intelligence

March 22-24, 2010, Stanford, CA

NEW!: the Symposium program(pdf) is available. HTML to follow.

The goal of Linked Data is to enable people to share structured data on the Web as easily as they can share documents today. The basic assumption behind Linked Data is that the value and usefulness of data increases the more it is interlinked with other data. Linked Data is simply about using the Web to create typed links between data from different sources. Today, this emerging Web of Data includes data sets as extensive and diverse as DBpedia, Geonames, US Census, EuroStat, MusicBrainz, BBC Programmes, Flickr, DBLP, PubMed, UniProt, FOAF, SIOC, OpenCyc, UMBEL, Virtual Observatories, and Yago.

The availability of this linked data creates a new opportunity for the exploitation of AI techniques that have historically played central role in knowledge representation, information extraction, information integration, and cognitive agents. The symposium is aimed at bringing together the researchers working on Linked Data and AI. Our hope is to create a new community interested in utilizing AI techniques such as ontologies, machine learning, data fusion, etc. in exploring the linked open data. Successful submissions will address at least some aspect of both areas.

The symposium will cover topics such as:

  • Light Weight Ontologies for Linked Data
  • Lightweight representation languages for capturing linked data
  • Lightweight ontologies to specify semantics in linked data
  • Conceptual modeling techniques for representing linked data
  • Ontology community evolution and maintenance environments for use with linked data
  • Ontology-enabled environments and tools for Linked Data
Semantic Publishing
  • Tools for publishing large data sources using light weight ontologies on the Web (e.g. relational databases, XML repositories)
  • Curating policies and approaches for linked data
  • Embedding linked data with semantics into classic Web documents (e.g. GRDDL, RDFa, Microformats)
  • Licensing and provenance tracking issues in Linked Data publishing Provenance languages and tools for Linked Data
  • Business models for Linked Data publishing and consumption
Exploiting Linked Data
  • User interaction and usability issues surrounding linked data
  • Visualization techniques for exploring linked data
  • Evidence-weighing techniques for socially-grounded claims (FOAF, OpenID)
  • Use of machine learning algorithms for linking and identity resolution
  • Inference and techniques for answering questions using linked data
  • Exploiting rich knowledge bases in conjunction with the linked data
Linked Data Application Architectures
  • Crawling, caching and querying Linked Data on the Web; optimizations, performance
  • Linked Data browsers
  • Linked Data search engines and search interfaces
  • Building intelligent agents that exploit linked data

The symposium will feature contributed papers, invited talks, and panels, and will include "self-organized" sessions in the barcamp / un-conference style.

Email contact:

Keynote: R.V. Guha (Google)


We welcome short and long papers, position statements, videos, panel and demo proposals. Please submit your paper of 2-6 pages in PDF AAAI submission format (available here) to the Linked Data and AI submission site on Easychair.

Important Dates Note that deadline has been extended two weeks from the original Oct 2nd deadline.
  • October 16, 2009: Submissions due to organizers
  • November 20, 2009: Notification of acceptance sent by organizers
  • January 22, 2010: Accepted camera-ready copy due to AAAI
Organizing Committee

Dan Brickley (VU University Amsterdam), Vinay K. Chaudhri (SRI International), Harry Halpin (University of Edinburgh), Deborah McGuinness (Rensselaer Polytechnic Institute).

Program Committee
  • Ji Bao (Rensselaer Polytechnic Institute)
  • Chris Bizer (Freie Universitat Berlin)
  • Paolo Bouqeut (University of Trento)
  • Richard Cyganiak (DERI)
  • Adam Cheyer (Siri)
  • Mariano Consens (Toronto)
  • Dan Connolly (W3C)
  • Li Ding (Rensselaer Polytechnic Institute)
  • An Hai Doan (University of Wisconsin at Madison)
  • Orri Erling (OpenLink Software)
  • Richard Fikes (Stanford University)
  • Tom Gruber (Siri)
  • R.V. Guha (Google)
  • Andreas Harth (Karlsruhe)
  • Pat Hayes (IMHC)
  • Tom Heath (Talis)
  • Jeff Heflin (Lehigh University)
  • Martin Hepp (Universitaet der Bundeswehr Muenchen)
  • Jim Hendler (Rensselaer Polytechnic Institute)
  • Ivan Herman (W3C)
  • Michael Hausenblas (DERI)
  • Raphael Hoffmann (University of Washington at Seattle)
  • David Israel (SRI International)
  • Lalana Kagal (MIT)
  • Michael Kassoff (Stanford)
  • Craig Knoblock (ISI)
  • Peter Mika (Yahoo)
  • Libby Miller (BBC)
  • Renee Miller (University of Toronto, Canada)
  • Steve Minton (Fetch Technologies)
  • Enrico Motta (Open University)
  • Peter Murray-Rust (Cambridge University)
  • Mark Musen (Stanford University)
  • Axel Polleres (DERI)
  • Nigel Shadbolt (University of Southhampton)
  • Nova Spivak (Radar)
  • York Sure (GESIS - Leibniz Institute for Social Sciences)
  • Jamie Taylor (Metaweb)
  • Mischa Tuffield (Garlik)
  • Henry Thompson (University of Edinburgh)
  • Evelyne Viegas (Microsoft)
  • Chris Welty (IBM)
  • Michael Witbrock (Cycorp)
  • Guizhen Yang (Facebook)
  • Jun Zhao (Oxford University)
    program.pdf18.74 KB