Data linking for the Semantic Web

By specifying that published datasets must link to other existing datasets, the 4th linked data principle ensures a Web of data and not just a set of unconnected data islands. The authors propose in this paper the term data linking to name the problem of finding equivalent resources on the Web of linked data. In order to perform data linking, many techniques were developed, finding their roots in statistics, database, natural language processing and graph theory. The authors begin this paper by providing background information and terminological clarifications related to data linking. Then a comprehensive survey over the various techniques available for data linking is provided. These techniques are classified along the three criteria of granularity, type of evidence, and source of the evidence. Finally, the authors survey eleven recent tools performing data linking and we classify them according to the surveyed techniques

State of the Art on Ontology Alignment

Ontology mapping as a semantic data integration approach has evolved from traditional data integration solutions. The core problems and open issues related to early data integration approaches are also applicable to ontology mapping on the Semantic Web community. Therefore, in this review the authors present the related literature, starting from the traditional data integration approaches, in order to highlight the evolution of data integration from the early approaches. Once the roots of semantic data integration have been presented, the authors proceed to introduce the state-of-the-art of the ontology mappings systems including the early approaches and the systems that can be compared through the Ontology Alignment Initiative (OAEI)