An increasing number of research and industrial initiatives have focused on publishing Linked Open Data, but little attention has been provided to help consumers to better understand existing data sets. In this paper we discuss how an ontology-driven data abstraction model supports the extraction and the representation of summaries of linked data sets. The proposed summarization model is the backbone of the ABSTAT framework, that aims at helping users understanding big and complex linked data sets. The proposed model produces a summary that is correct and complete with respect to the assertions of the data set and whose size scales well with respect to the ontology and data size. Our framework is evaluated by showing that it is capable of unveiling information that is not explicitly represented in underspecified ontologies and that is valuable to users, e.g., helping them in the formulation of SPARQL queries.

Spahiu, B., Porrini, R., Palmonari, M., Rula, A., Maurino, A. (2016). ABSTAT: Ontology-driven linked data summaries with pattern minimalization. In SEMANTIC WEB, ESWC 2016 (pp.381-395). Springer Verlag [10.1007/978-3-319-47602-5_51].

ABSTAT: Ontology-driven linked data summaries with pattern minimalization

SPAHIU, BLERINA
;
PORRINI, RICCARDO;PALMONARI, MATTEO LUIGI;RULA, ANISA;MAURINO, ANDREA
2016

Abstract

An increasing number of research and industrial initiatives have focused on publishing Linked Open Data, but little attention has been provided to help consumers to better understand existing data sets. In this paper we discuss how an ontology-driven data abstraction model supports the extraction and the representation of summaries of linked data sets. The proposed summarization model is the backbone of the ABSTAT framework, that aims at helping users understanding big and complex linked data sets. The proposed model produces a summary that is correct and complete with respect to the assertions of the data set and whose size scales well with respect to the ontology and data size. Our framework is evaluated by showing that it is capable of unveiling information that is not explicitly represented in underspecified ontologies and that is valuable to users, e.g., helping them in the formulation of SPARQL queries.
paper
data summarization, knowledge patterns, linked data
English
European Semantic Web Conference (ESWC) MAY 29-JUN 02
2016
Sack, H; Rizzo, G; Steinmetz, N; Mladenic, D; Auer, S; Lange, C
SEMANTIC WEB, ESWC 2016
9783319476018
2016
9989
381
395
https://link.springer.com/chapter/10.1007/978-3-319-47602-5_51
partially_open
Spahiu, B., Porrini, R., Palmonari, M., Rula, A., Maurino, A. (2016). ABSTAT: Ontology-driven linked data summaries with pattern minimalization. In SEMANTIC WEB, ESWC 2016 (pp.381-395). Springer Verlag [10.1007/978-3-319-47602-5_51].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/118069
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