Visualizing, Exploring and Analyzing Big Data: A 6-Year Story-Reference-Cited by-同舟云学术

Visualizing, Exploring and Analyzing Big Data: A 6-Year Story

Published:2024-07-30 Issue:2 Volume:53 Page:54-57
ISSN:0163-5808
Container-title:ACM SIGMOD Record
language:en
Short-container-title:SIGMOD Rec.

Author:

Bikakis Nikos¹,Papastefanatos George²,Chrysanthis Panos K.³,Papemmanuil Olga⁴,Auber David⁵,Frey Steffen⁶,Fujishiro Issei⁷,Hauptmann Hanna⁸,Liu Shixia⁶,Ma Kwan-Liu⁹,Schreck Tobias¹⁰,Sedlmair Michael¹¹,Sharaf Mohamed A.¹²

Affiliation:

1. Hellenic Mediterranean University, Greece

2. ATHENA Research Center, Greece

3. University of Pittsburgh, Pittsburgh, PA, USA

4. Brandeis University, Waltham, MA, USA

5. University Bordeaux, France

6. University of Groningen, Netherlands

7. Keio University, Japan

8. Utrecht University, Netherlands

9. University of California-Davis, CA, USA

10. Graz University of Technology, Austria

11. University of Stuttgart, Germany

12. United Arab Emirates University, UAE

Abstract

Information Visualization has been one of the cornerstones of Data Science, turning the abundance of Big Data being produced through modern systems into actionable knowledge. Indeed, the Big Data era has realized the availability of voluminous datasets that are dynamic, multidimensional, noisy and heterogeneous in nature. Transforming a data-curious user into someone who can access and analyze that data is even more burdensome now for a great number of users with little or no support and expertise on the data processing part.

Publisher

Association for Computing Machinery (ACM)

Link

https://dl.acm.org/doi/pdf/10.1145/3685980.3685994

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