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Authors: Jakub Klímek 1 ; Martin Nečaský 1 ; Bogdan Kostov 2 ; Miroslav Blaško 2 and Petr Křemen 2

Affiliations: 1 Charles University in Prague, Czech Republic ; 2 Czech Technical University in Prague, Czech Republic

Keyword(s): Linked Data, RDF, SPARQL, Exploration, Visualization.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Business Analytics ; Collaboration and e-Services ; Corporate Semantic Web ; Data Analytics ; Data Engineering ; Data Management and Quality ; Data Modeling and Visualization ; Databases and Data Security ; e-Business ; Enterprise Information Systems ; Information Integration ; Information Retrieval ; Information Systems Analysis and Specification ; Integration/Interoperability ; Knowledge Discovery and Information Retrieval ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Modeling and Managing Large Data Systems ; Ontologies and the Semantic Web ; Ontology Engineering ; Open Data ; Pattern Recognition ; Software Engineering ; Symbolic Systems ; Web Analytics ; WWW and Databases

Abstract: As the size of semantic data available as Linked Open Data (LOD) increases, the demand for methods for automated exploration of data sets grows as well. A data consumer needs to search for data sets meeting his interest and look into them using suitable visualization techniques to check whether the data sets are useful or not. In the recent years, particular advances have been made in the field, e.g., automated ontology matching techniques or LOD visualization platforms. However, an integrated approach to LOD exploration is still missing. On the scale of the whole web, the current approaches allow a user to discover data sets using keywords or manually through large data catalogs. Existing visualization techniques presume that a data set is of an expected type and structure. The aim of this position paper is to show the need for time and space efficient techniques for discovery of previously unknown LOD data sets on the base of a consumer’s interest and their automated visualization which we address in our ongoing work (More)


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Paper citation in several formats:
Klímek, J.; Nečaský, M.; Kostov, B.; Blaško, M. and Křemen, P. (2015). Efficient Exploration of Linked Data Cloud. In Proceedings of 4th International Conference on Data Management Technologies and Applications - DATA, ISBN 978-989-758-103-8; ISSN 2184-285X, pages 255-261. DOI: 10.5220/0005558002550261

author={Jakub Klímek. and Martin Nečaský. and Bogdan Kostov. and Miroslav Blaško. and Petr K\v{r}emen.},
title={Efficient Exploration of Linked Data Cloud},
booktitle={Proceedings of 4th International Conference on Data Management Technologies and Applications - DATA,},


JO - Proceedings of 4th International Conference on Data Management Technologies and Applications - DATA,
TI - Efficient Exploration of Linked Data Cloud
SN - 978-989-758-103-8
IS - 2184-285X
AU - Klímek, J.
AU - Nečaský, M.
AU - Kostov, B.
AU - Blaško, M.
AU - Křemen, P.
PY - 2015
SP - 255
EP - 261
DO - 10.5220/0005558002550261