This document summarizes an approach for identifying external data repositories that contain relevant data to link to a new dataset using a semantic web index. The approach searches for repositories with potentially overlapping data, ranks them by number of matching entities, and selects the best matching class within each repository. Preliminary experiments show filtering search results by relevant classes using schema matching improves precision of the top-ranked repositories, though some recall is lost. Future work includes improving result quality and integrating the approach into the full data linking workflow.

1. Identifying Relevant Sources for Data Linking using a Semantic Web Index Andriy Nikolov Mathieu d’Aquin Knowledge Media Institute The Open University, UK