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Conference Papers Year : 2021

From Linked Data Querying to Visual Search: Towards a Visualization Pipeline for LOD Exploration

Abstract

Over the recent years, Linked Open Data (LOD) has been increasingly used to support decision-making processes in various application domains. For that purpose, an increasing interest in information visualization has been observed in the literature as a suitable solution to communicate the knowledge described in LOD data sources. Nonetheless, transforming raw LOD data into a graphical representation (the so-called visualization pipeline) is not a straightforward process and often requires a set of operations to transform data into meaningful visualizations that suit users' needs. In this paper, we propose a LOD generic visualization pipeline and discuss the implications of the internal operations (import → transform → map → render → interact) for creating meaningful visualizations of LOD datasets. To demonstrate the feasibility of this generic visualization pipeline, we implement it as the tool LDViz (Linked Data Visualizer). We demonstrate how LDViz supports access to any SPARQL endpoint through multiple use cases, allowing the users to perform searches with SPARQL queries and visualize the results using multiple visualization techniques.
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Dates and versions

hal-03404572 , version 1 (26-10-2021)

Identifiers

Cite

Aline Menin, Catherine Faron, Olivier Corby, Carla Maria Dal Sasso Freitas, Fabien Gandon, et al.. From Linked Data Querying to Visual Search: Towards a Visualization Pipeline for LOD Exploration. WEBIST 2021 - 17th International Conference on Web Information Systems and Technologies, Oct 2021, Online Streaming, France. ⟨10.5220/0010654600003058⟩. ⟨hal-03404572⟩
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