To extend the scope of retrieval and reasoning spanning several linked data stores, it is necessary to find out whether information in different collections actually points to the same real world object. Thus, data stores are interlinked through owl:sameAs relations. Unfortunately, this cross-linkage is not as extensive as one would hope. To remedy this problem, instance matching systems automatically discovering owl:sameAs links, have been proposed recently. According to results on existing benchmarks, such systems seem to have reached a convincing level of maturity. But the evaluations miss out on some important characteristics encountered in real-world data. To establish if instance matching systems are really ready for real-world data interlinking, we analyzed the main challenges of instance matching. We built a representative data set that emphasizes these challenges and evaluated the global quality of instance matching systems on the example of a top performer from last year's Instance Matching track organized by the Ontology Alignment Evaluation Initiative (OAEI). © 2014 Springer International Publishing.
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014|
|Period||25/06/14 → 27/06/14|