Section: New Results
Ontology matching and alignment
We pursue our work work on ontology matching and alignment support with basic contributions.
Evaluation
Participants : Cássia Trojahn dos Santos [ Contact ] , Jérôme Euzenat, Jérôme David.
Evaluation of ontology matching algorithms involves to confront them with test ontologies and to compare the results. Since 2004, we run the the Ontology Alignment Evaluation Initiative (OAEI) which organises evaluation campaigns for assessing the degree of achievement of actual ontology matching algorithms. This year, the evaluation campaign had 16 different teams entered the evaluation which consisted of 9 different sets of tests. The participating systems and evaluation results were presented in the Fourth Workshop on Ontology Matching, that has been held in Virginia, USA [17] [8] .
More information on OAEI can be found at http://oaei.ontologymatching.org/ .
Ontology distances
Participants : Jérôme David [ Contact ] , Jérôme Euzenat, Ondrej Zamazal.
Measuring similarity between ontologies can be very important in various tasks with different purposes. Last year we have implementated and experimented with classical measures; this year, we have introduced a new family of ontology measures: they are said to be computed in the alignment space, by contrast with more classical measures working in the ontology space. Measures working in the alignment space evaluate the similarity between two ontologies with regard to the available alignments between them. We introduce two sets of such measures relying on the existence of path between ontologies or on the ontology entities that are preserved by the alignments. This reflects the possibility to perform actions such as instance import or query translation. These measures have all been implemented in a library, OntoSim (§ 5.2 ), that has been used in experiments. The experiments shown that entity preserving measures are correlated with the best ontology space measures. Moreover they show a linear degradation with the alteration of alignments, witnessing their robustness [18] .
Pattern-based ontology matching
Participants : François Scharffe [ Contact ] , Jérôme David, Ondrej Zamazal.
Ontology patterns are abstractions of typical configurations within ontologies. They can be instantiated in particular ontologies. We have developed correspondence patterns which abstract typical correspondences between ontologies. They can be expressed in an expressive alignment language like the one embedded in the Alignment API (§ 5.1 )).
We have shown how correspondence patterns can be used for guiding the matching process [13] , for normalising ontologies before alignments or for transforming ontologies.
We have introduced the notion of an ontology transformation service. This service is supported by ontology transformation patterns consisting of corresponding ontology patterns, capturing alternative modelling choices, and an alignment between them. The transformation process is made of two steps: a pattern detection and an ontology transformation process. Pattern detection is based on SPARQL [11] and transformation is based on an ontology alignment representation with specific detailed information about the transformation [14] .
We also plan to apply such ontology matching techniques to instance matching for the inference in linked data [12] .
