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  1. Research Outputs

Empirical Evaluation of Linked Data Visualization Tools

Academic Article
Publication Date:
2020
Short description:
Empirical Evaluation of Linked Data Visualization Tools / Desimoni, Federico; Po, Laura. - In: FUTURE GENERATION COMPUTER SYSTEMS. - ISSN 0167-739X. - 112:(2020), pp. 258-282. [10.1016/j.future.2020.05.038]
abstract:
The economic impact of open data in Europe has an estimated value of €140 billions a year between direct and indirect effects. The social impact is also known to be high, as the use of more transparent open data have been enhancing public services and creating new opportunities for citizens and organizations. We are assisting at a staggering growth in the production and consumption of Linked Data (LD). Exploring, visualizing and analyzing LD is a core task for a variety of users in numerous scenarios. This paper deeply analyzes the state of the art of tools for LD visualization. Linked Data visualization aims to provide graphical representations of datasets or of some information of interest selected by a user, with the aim to facilitate their analysis. A complete list of 77 LD visualization tools has been created starting from tools listed in previous surveys or research papers and integrating newer tools recently published online. The visualization tools have been described and compared based on their usability, and their features. A set of goals that LD tools should implement in order to provide clear and convincing visualizations has been defined and 14 tools have been tested on a big LD dataset. The results of this comparison and test led us to define some suggestions for LD consumers in order for them to be able to select the most appropriate tools based on the type of analysis they wish to perform.
Iris type:
Articolo su rivista
Keywords:
Linked Data Visualization tools Open data Linked data exploration guidelines
List of contributors:
Desimoni, Federico; Po, Laura
Authors of the University:
PO Laura
Handle:
https://iris.unimore.it/handle/11380/1203405
Published in:
FUTURE GENERATION COMPUTER SYSTEMS
Journal
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