Section: New Results

Interacting with Linked Data and the Semantic Web

• As part of the team's novel research theme on Semantics-Driven Data Manipulation 3.2, Emmanuel Pietriga worked jointly with colleagues from Linköping University on a visualization technique for the comparative evaluation of ontology alignments produced by different algorithms, that was published at the International Semantic Web Conference [21]. Ontology alignment is an area of active research where many algorithms and approaches are being developed. Their performance is usually evaluated by comparing the produced alignments to a reference alignment in terms of precision, recall and F-measure. These measures, however, only provide an overall assessment of the quality of the alignments, but do not reveal differences and commonalities between alignments at a finer-grained level such as, e.g., regions or individual mappings. Furthermore, reference alignments are often unavailable, which makes the comparative exploration of alignments at different levels of granularity even more important. Making such comparisons efficient calls for a human-in-the-loop approach, best supported through interactive visual representations of alignments. Our approach extended previous work by Inria on Matrix Cubes  [32], used for visualizing dense dynamic networks. We identified use cases for ontology alignment evaluation that could benefit from interactive visualization, and then detailed how Alignment Cubes could support interactive exploration of multiple ontology alignments. We then showed how alignment cubes could support common tasks identified in these use cases.