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

Nikos Bikakis; George Papastefanatos; Panos K. Chrysanthis; Olga Papemmanuil; David Auber; Steffen Frey; Issei Fujishiro; Hanna Hauptmann; Shixia Liu; Kwan Liu Ma; Tobias Schreck; Michael Sedlmair; Mohamed A. Sharaf

doi:10.1145/3685980.3685994

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

Nikos Bikakis, George Papastefanatos, Panos K. Chrysanthis, Olga Papemmanuil, David Auber, Steffen Frey, Issei Fujishiro, Hanna Hauptmann, Shixia Liu, Kwan Liu Ma, Tobias Schreck, Michael Sedlmair, Mohamed A. Sharaf

Department of Computer Science and Software Engineering

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	54-57
Number of pages	4
Journal	SIGMOD Record
Volume	53
Issue number	2
DOIs	https://doi.org/10.1145/3685980.3685994
Publication status	Published - Jul 31 2024

ASJC Scopus subject areas

Software
Information Systems

Access to Document

10.1145/3685980.3685994

Cite this

@article{6fe4ccc141e14652ae12f5ccd631323b,

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

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.",

author = "Nikos Bikakis and George Papastefanatos and Chrysanthis, {Panos K.} and Olga Papemmanuil and David Auber and Steffen Frey and Issei Fujishiro and Hanna Hauptmann and Shixia Liu and Ma, {Kwan Liu} and Tobias Schreck and Michael Sedlmair and Sharaf, {Mohamed A.}",

note = "Publisher Copyright: {\textcopyright} 2024 Copyright is held by the owner/author(s)",

year = "2024",

month = jul,

day = "31",

doi = "10.1145/3685980.3685994",

language = "English",

volume = "53",

pages = "54--57",

journal = "SIGMOD Record",

issn = "0163-5808",

publisher = "Association for Computing Machinery (ACM)",

number = "2",

}

TY - JOUR

T1 - Visualizing, Exploring and Analyzing Big Data

T2 - A 6-Year Story

AU - Bikakis, Nikos

AU - Papastefanatos, George

AU - Chrysanthis, Panos K.

AU - Papemmanuil, Olga

AU - Auber, David

AU - Frey, Steffen

AU - Fujishiro, Issei

AU - Hauptmann, Hanna

AU - Liu, Shixia

AU - Ma, Kwan Liu

AU - Schreck, Tobias

AU - Sedlmair, Michael

AU - Sharaf, Mohamed A.

PY - 2024/7/31

Y1 - 2024/7/31

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85200590944&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85200590944&partnerID=8YFLogxK

U2 - 10.1145/3685980.3685994

DO - 10.1145/3685980.3685994

M3 - Article

AN - SCOPUS:85200590944

SN - 0163-5808

VL - 53

SP - 54

EP - 57

JO - SIGMOD Record

JF - SIGMOD Record

IS - 2

ER -

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

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this