Generating structured Profiles of Linked Data Graphs
Besnik Fetahu, Stefan Dietze, Bernardo Pereira Nunes, Davide Taibi, Marco A. Casanova · 2014
Abstract. While there exists an increasingly large number of Linked Data, metadata about the content covered by individual datasets is sparse. In this paper, we introduce a processing pipeline to automatically assess, annotate and index available linked datasets. Given a minimal description of a dataset from the DataHub, the process produces a structured RDF-based description that includes information about its main topics. Additionally, the generated descriptions embed datasets into an interlinked graph of datasets based on shared topic vocabularies. We adopt and integrate techniques for Named Entity Recognition and automated data validation, providing a consistent workflow for dataset profiling and annotation. Finally, we validate the results obtained with our tool.