Data di Pubblicazione:
2013
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 auto- mated data validation, providing a consistent work ow for dataset profiling and annotation. Finally, we validate the results obtained with our tool.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Linked Data; Annotation; Datasets; Metadata
Elenco autori:
Taibi, Davide
Link alla scheda completa:
Titolo del libro:
Proceedings of the ISWC 2013 Posters & Demonstrations Track
Pubblicato in: