Artificial Intelligence meets the Web of Data

The Linked Data initiative aims at improving data publication on the Web, thereby creating a “Web of Data”: an interconnected, distributed, global data space. The Web of Data enables people to share structured data on the Web as easily as they can currently share documents on the Web of Documents (WWW). The basic assumption behind the Web of Data is that the value and usefulness of data increases with the amount of interlinking with other data. The emerging Web of Data includes datasets as extensive and diverse as DBpedia, Flickr, and DBLP. A “tip of the iceberg” representation of its content is behind maintained at

The availability of this global data space creates new opportunities for the exploitation of Artificial Intelligence techniques in relation with knowledge representation, information extraction, information integration, and intelligent agents. Two approaches can emerge: (i) using AI techniques to address the problems the Web of Data faces or, (ii) using the design principles of the Web of Data to improve knowledge representation within AI techniques.

The workshop aims at bringing together researchers and practitioners working on the Web of Data and/or Artificial Intelligence to discuss the union of these two research areas. Several core challenges, such as the interconnection of heterogeneous datasets, the provenance of the information and trust issues will be at the centre of the discussion. With this workshop, our goal is to contribute to the birth of a community having a shared interest around publishing data on the Web and exploring it using AI technologies – or the inverse, developing and improving AI technologies which use tools from the Web of Data.

PROGRAM - August 27th 2012

9:00 - 9:10 Opening Workshop

9:10 - 10:10 Invited Speaker: Jerome Euzenat - The Web of Data as an AI playground


The web of data can be seen as an answer to the semantic web's lack of data. It has finally provided the amount of data with which the developed semantic technologies become useful. It also brings the expected challenges of scalability, heterogeneity, unreliability all occurring together. I will illustrate how the web of data can be considered as an available playground for reasoning and machine learning in the large. I will also try to point out the benefit of having a web of data in order to improve the results provided by AI methods.

10:10 - 10:30 Coffee break

10:30 - 12:30 Contributed Talks (20 minutes talk, 10 minutes questions)

Bridging the Gap between RIF and SPARQL: Implementation of a RIF Dialect with a SPARQL Rule Engine

Seye, Faron Zucker, Corby, Follenfant

Implementation of a SPARQL Integrated Recommendation Engine for Linked Data with Hybrid Capabilities

Policarpio, Brunk, Tummarello

Diamond: A SPARQL Query Engine, for Linked Data Based on the Rete Match

Miranker, Depena, Jung, Sequeda, Reyna

Vocabutek: An Electronic Auction of Knowledge for Linked Data

Halpin, Reck

12:40 - 14:30 Lunch

14:30 - 15:30 Invited Speaker: Philippe Cudré-Mauroux - Emergent Semantics for Graph Data Integration


Emergent semantics techniques model the semantics of a distributed system as an ensemble of relationships between syntactic structures. They consider both the representation of semantics and the discovery of the proper interpretation of symbols as the result of a self-organizing process performed by distributed agents exchanging symbols and having utilities dependent on the proper interpretation of the symbols. In this talk, I will introduce the notion of emergent semantics and describe a series of emergent semantics applications focusing on entity matching for semi-structured graph data. 

15:30 Closing Workshop