Exploring LOD through metadata extraction and data-driven visualizations
Program: electronic library and information systems
ISSN: 0033-0337
Article publication date: 4 July 2016
Abstract
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.
Keywords
Citation
Peña, O., Aguilera, U. and López-de-Ipiña, D. (2016), "Exploring LOD through metadata extraction and data-driven visualizations", Program: electronic library and information systems, Vol. 50 No. 3, pp. 270-287. https://doi.org/10.1108/PROG-12-2015-0079
Publisher
:Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited