Data Linking for the Semantic Web

Abstract

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.

Keys and Pseudo-Keys Detection for Web Datasets Cleansing and Interlinking

“…4 Manual analysis confirmed several kinds of errors. A first type of error is due to the existence of resources describing the same object.…”

Automatic Key Selection for Data Linking

“…Here, instead of making an inventory of these techniques, surveyed in [12] and [13], we scrutinize the main characteristics that unite or differentiate the most common approaches.…”

Data Linking with Ontology Alignment

“…Formally, data linking is an operation whose input are two collections of data. Its output is a collection of links between entities from both collections, in which there are binary relations on entities corresponding semantically to each other [4]. So, the research problem which will be tackled here is: given two RDF data sets, try to find out all possible "owl:sameAs" links between them automatically and correctly.…”