The number and the size of Linked Data sources are constantly increasing. In some lucky case, the data source is equipped with a tool that guides and helps the user during the exploration of the data, but in most cases, the data are published as an RDF dump through a SPARQL endpoint that can be accessed only through SPARQL queries. Although the RDF format was designed to be processed by machines, there is a strong need for visualization and exploration tools. Data visualizations make big and small linked data easier for the human brain to understand, and visualization also makes it easier to detect patterns, trends, and outliers in groups of data. For this reason, we developed a tool called H-BOLD (Highlevel Visualization over Big Linked Open Data). H-BOLD aims to help the user exploring the content of a Linked Data by providing a high-level view of the structure of the dataset and an interactive exploration that allows users to focus on the connections and attributes of one or more classes. Moreover, it provides a visual interface for querying the endpoint that automatically generates SPARQL queries.

Providing effective visualizations over big linked data / Desimoni, Federico; Po, Laura. - (2020). (Intervento presentato al convegno Workshops of the 23rd International Conference on Extending Database Technology/23rd International Conference on Database Theory, EDBT-ICDT-WS 2020 tenutosi a Copenhagen, Denmark nel 30 March 2020 - 2 April 2020).

Providing effective visualizations over big linked data

Federico Desimoni
;
Laura Po
2020

Abstract

The number and the size of Linked Data sources are constantly increasing. In some lucky case, the data source is equipped with a tool that guides and helps the user during the exploration of the data, but in most cases, the data are published as an RDF dump through a SPARQL endpoint that can be accessed only through SPARQL queries. Although the RDF format was designed to be processed by machines, there is a strong need for visualization and exploration tools. Data visualizations make big and small linked data easier for the human brain to understand, and visualization also makes it easier to detect patterns, trends, and outliers in groups of data. For this reason, we developed a tool called H-BOLD (Highlevel Visualization over Big Linked Open Data). H-BOLD aims to help the user exploring the content of a Linked Data by providing a high-level view of the structure of the dataset and an interactive exploration that allows users to focus on the connections and attributes of one or more classes. Moreover, it provides a visual interface for querying the endpoint that automatically generates SPARQL queries.
2020
mar-2020
Workshops of the 23rd International Conference on Extending Database Technology/23rd International Conference on Database Theory, EDBT-ICDT-WS 2020
Copenhagen, Denmark
30 March 2020 - 2 April 2020
Desimoni, Federico; Po, Laura
Providing effective visualizations over big linked data / Desimoni, Federico; Po, Laura. - (2020). (Intervento presentato al convegno Workshops of the 23rd International Conference on Extending Database Technology/23rd International Conference on Database Theory, EDBT-ICDT-WS 2020 tenutosi a Copenhagen, Denmark nel 30 March 2020 - 2 April 2020).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1201074
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