The Linked Open Data (LOD) Cloud is continuously expanding and the number of complex and large sources is raising. Understanding at a glance an unknown source is a critical task for LOD users but it can be facilitated by visualization or exploration tools. H-BOLD (High-level visualization over Big Open Linked Data) is a tool that allows users with no a-priori knowledge on the domain nor SPARQL skills to start navigating and exploring Big Linked Data. Users can start from a high-level visualization and then focus on an element of interest to incrementally explore the source, as well as perform a visual query on certain classes of interest. At the moment, 32 Big Linked Data (with more than 500.000 triples) exposing a SPARQL endpoint can be explored by using H-BOLD.

High-level visualization over big linked data / Po, Laura; Malvezzi, Davide. - 2180:(2018). (Intervento presentato al convegno 17th International Semantic Web Conference (ISWC 2018) tenutosi a Monterey, California, USA nel 8-12 October, 2018).

High-level visualization over big linked data

Po, Laura;
2018

Abstract

The Linked Open Data (LOD) Cloud is continuously expanding and the number of complex and large sources is raising. Understanding at a glance an unknown source is a critical task for LOD users but it can be facilitated by visualization or exploration tools. H-BOLD (High-level visualization over Big Open Linked Data) is a tool that allows users with no a-priori knowledge on the domain nor SPARQL skills to start navigating and exploring Big Linked Data. Users can start from a high-level visualization and then focus on an element of interest to incrementally explore the source, as well as perform a visual query on certain classes of interest. At the moment, 32 Big Linked Data (with more than 500.000 triples) exposing a SPARQL endpoint can be explored by using H-BOLD.
2018
17th International Semantic Web Conference (ISWC 2018)
Monterey, California, USA
8-12 October, 2018
2180
Po, Laura; Malvezzi, Davide
High-level visualization over big linked data / Po, Laura; Malvezzi, Davide. - 2180:(2018). (Intervento presentato al convegno 17th International Semantic Web Conference (ISWC 2018) tenutosi a Monterey, California, USA nel 8-12 October, 2018).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1169199
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