Open Data Integration - Visualization as an Asset

Carvalho, Paulo da Silva; Hitzelberger, Patrik; Otjacques, Benoît; Bouali, Fatma; Venturini, Gilles

doi:10.5220/0005000600410047

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…As stated by (Carvalho et al 2014), "Metadata provides the means to discover datasets, access them and understand them". By definition, metadata exposes an abstraction on the dataset itself, thus different tools have relied on metadata extraction in order to comply with InfoVis Mantra's first visualization task: Overview (Shneiderman 1996).…”

Section: Focusing On Relevant Conceptsmentioning

confidence: 99%

Exploring LOD through metadata extraction and data-driven visualizations

Peña

Aguilera

López-de-Ipiña

2016

Program

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Purpose – The purpose of this paper is to present a new approach toward automatically visualizing Linked Open Data (LOD) through metadata analysis. Design/methodology/approach – By focussing on the data within a LOD dataset, the authors can infer its structure in a much better way than current approaches, generating more intuitive models to progress toward visual representations. Findings – With no technical knowledge required, focussing on metadata properties from a semantically annotated dataset could lead to automatically generated charts that allow to understand the dataset in an exploratory manner. Through interactive visualizations, users can navigate LOD sources using a natural approach, in order to save time and resources when dealing with an unknown resource for the first time. Research limitations/implications – This approach is suitable for available SPARQL endpoints and could be extended for resource description framework dumps loaded locally. Originality/value – Most works dealing with LOD visualization are customized for a specific domain or dataset. This paper proposes a generic approach based on traditional data visualization and exploratory data analysis literature.

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Section: Focusing On Relevant Conceptsmentioning

confidence: 99%