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Authors: Enrico G. Caldarola 1 and Antonio M. Rinaldi 2

Affiliations: 1 University of Naples Federico II and National Research Council, Italy ; 2 University of Naples Federico II, Italy

ISBN: 978-989-758-255-4

Keyword(s): Big Data, Big Data Visualization, Graph Visualization, Information Visualization, Big Data Analytics, Visual Analytics.

Abstract: In the era of Big Data, a great attention deserves the visualization of large data sets. Among the main phases of the data management’s life cycle, i.e., storage, analytics and visualization, the last one is the most strategic since it is close to the human perspective. The huge mine of data becomes a gold mine only if tricky and wise analytics algorithms are executed over the data deluge and, at the same time, the analytic process results are visualized in an effective, efficient and why not impressive way. Not surprisingly, a plethora of tools and techniques have emerged in the last years for Big Data visualization, both as part of Data Management Systems or as software or plugins specifically devoted to the data visualization. Starting from these considerations, this paper provides a survey of the most used and spread visualization tools and techniques for large data sets, eventually presenting a synoptic of the main functional and non-functional characteristics of the surv eyed tools. (More)

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Paper citation in several formats:
Caldarola , E. and Rinaldi, A. (2017). Big Data Visualization Tools: A Survey - The New Paradigms, Methodologies and Tools for Large Data Sets Visualization.In Proceedings of the 6th International Conference on Data Science, Technology and Applications - Volume 1: KomIS, ISBN 978-989-758-255-4, pages 296-305. DOI: 10.5220/0006484102960305

@conference{komis17,
author={Enrico G. Caldarola . and Antonio M. Rinaldi.},
title={Big Data Visualization Tools: A Survey - The New Paradigms, Methodologies and Tools for Large Data Sets Visualization},
booktitle={Proceedings of the 6th International Conference on Data Science, Technology and Applications - Volume 1: KomIS,},
year={2017},
pages={296-305},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006484102960305},
isbn={978-989-758-255-4},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Data Science, Technology and Applications - Volume 1: KomIS,
TI - Big Data Visualization Tools: A Survey - The New Paradigms, Methodologies and Tools for Large Data Sets Visualization
SN - 978-989-758-255-4
AU - Caldarola , E.
AU - Rinaldi, A.
PY - 2017
SP - 296
EP - 305
DO - 10.5220/0006484102960305

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