Linked Data Meets Artificial Intelligence
Papers from the AAAI Spring Symposium
Dan Brickley, Vinay K. Chaudhri, Harry Halpin, and Deborah McGuinness, Cochairs
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. 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 a central role in knowledge representation, information extraction, information integration, and cognitive agents. The symposium was aimed at bringing together researchers working on linked data and AI. The technical report includes papers on the topics of representing, browsing, querying, and applying AI methods to linked data.