Exploration and Visualization of Big Graphs - The DBpedia Case Study

Enrico G. Caldarola, Antonio Picariello, Antonio M. Rinaldi, Marco Sacco

2016

Abstract

Increasingly, the data and information visualization is becoming strategic for the exploration and explanation of large data sets. The Big Data paradigm pushes for new ways, new technological solutions to deal with the big volume and the big variety of data today. Not surprisingly, a plethora of new tools have emerged, each of them with pros and cons, but all espousing the cause of "Bigness of Data". In this paper, we take one of this emerging tools, namely Neo4J, and stress its capabilities in order to import, query and visualize data coming from a \emph{big} case study: DBpedia. We will describe each step in this study focusing on the used strategies for overcoming the different problems mainly due to the intricate nature of the case study and its volume. We confront with both the intensional schema of DBpedia and its extensional part in order to obtain the best result in its visualization. Finally, an attempt to define some criteria to simplify the large-scale visualization of DBpedia will be made, providing some examples and considerations which have arisen. The ultimate goal of this work is to investigate techniques and approaches to get more insights from the visual representation and analytics of large graph databases.

Paper Citation

in Harvard Style

G. Caldarola E., Picariello A., M. Rinaldi A. and Sacco M. (2016). Exploration and Visualization of Big Graphs - The DBpedia Case Study . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016) ISBN 978-989-758-203-5, pages 257-264. DOI: 10.5220/0006046802570264

in Bibtex Style

@conference{kdir16,
author={Enrico G. Caldarola and Antonio Picariello and Antonio M. Rinaldi and Marco Sacco},
title={Exploration and Visualization of Big Graphs - The DBpedia Case Study},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)},
year={2016},
pages={257-264},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006046802570264},
isbn={978-989-758-203-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)
TI - Exploration and Visualization of Big Graphs - The DBpedia Case Study
SN - 978-989-758-203-5
AU - G. Caldarola E.
AU - Picariello A.
AU - M. Rinaldi A.
AU - Sacco M.
PY - 2016
SP - 257
EP - 264
DO - 10.5220/0006046802570264