Section: New Results

Data interlinking

The web of data uses semantic web technologies to publish data on the web in such a way that they can be interpreted and connected together. It is thus important to be able to establish links between these data, both for the web of data and for the semantic web that it contributes to feed. We consider this problem from different perspectives.

Interlinking cross-lingual RDF data sets

Participants : Tatiana Lesnikova [Correspondent] , Jérôme David, Jérôme Euzenat.

rdf data sets are being published with labels that may be expressed in different languages. Even systems based on graph structure, ultimately rely on anchors based on language fragments. In this context, data interlinking requires specific approaches in order to tackle cross-lingualism. We proposed a general framework for interlinking rdf data in different languages and implemented two approaches: one approach is based on machine translation, the other one takes advantage of multilingual references, such as BabelNet. This year we investigated the second approach [10] , finding that results were not as good as the translation approach. We also conducted evaluations on TheSoz, Agrovoc and Eurovoc thesauri.

This work is part of the PhD of Tatiana Lesnikova developed in the Lindicle project (§ 9.1.1 ).

An iterative import-by-query approach to data interlinking

Participant : Manuel Atencia Arcas [Correspondent] .

We modelled the problem of data interlinking as a reasoning problem on possibly decentralised data. We described an import-by-query algorithm that alternates steps of sub-query rewriting and of tailored querying of data sources [11] . It only imports data as specific as possible for inferring or contradicting target owl:sameAs assertions. Experiments conducted on a real-world dataset have demonstrated in practice the feasibility and usefulness of this approach for data interlinking and disambiguation purposes.

Additionally, and in line with the problem of dealing with uncertainty in linked data, we have proposed a probabilistic mechanism of trust that allow peers in a semantic peer-to-peer network to select the peers that are better suited to answer their queries, when query reformulation based on alignments may be unsatisfactory due to unsoundness or incompleteness of alignments [5] .

This work was carried out in collaboration with Mustafa Al-Bakri and Marie-Christine Rousset (LIG).

Link key extraction

Participants : Jérôme David [Correspondent] , Manuel Atencia Arcas, Jérôme Euzenat.

Ontologies do not necessarily come with key descriptions, and never with link key assertions (§ 3.3 ). Keys can be extracted from data by assuming that keys holding for specific data sets, may hold universally.

Following the work of last year on link key extraction [1] and the characterisation of the approach in formal concept analysis, we have fully characterised the results of our algorithm as formal concepts. We have also plans for extending both the approach and its formal concept analysis description through (i) applying it to full link keys as described in § 3.3 , (ii) applying it to join and hierarchical key extraction, and (iii) applying it to hierarchical key extraction.

This work has been developed partly in the Lindicle project (§ 9.1.1 ). Formal concept analysis aspects are considered with Amedeo Napoli (Orpailleur, LORIA).