DocumentCode :
75209
Title :
Sharpening Analytic Focus to Cope with Big Data Volume and Variety
Author :
Shneiderman, Ben ; Plaisant, Catherine
Volume :
35
Issue :
3
fYear :
2015
fDate :
May-June 2015
Firstpage :
10
Lastpage :
14
Abstract :
The growing volumes of time-stamped data available from sensors, social media sources, Web logs, and medical histories present remarkable opportunities for researchers and policy analysts. Although big data resources can provide valuable insights to help us understand complex systems and lead to better decisions for business, national security, cybersecurity, and healthcare, there are many challenges to dealing with the volume and variety of data. Data cleaning and data wrangling has received some attention with the development of application tools, but data focusing to sharpen the analytic focus remains a challenge. To address this challenge, this article provides a taxonomy of analytic focusing strategies for temporal event sequences.
Keywords :
Big Data; data analysis; Big Data volume; analytic focusing strategies; data focusing; event sequences; Data visualization; Medical diagnostic imaging; Social network services; Visual analytics; analytic focusing; big data; computer graphics; data cleaning; visual analytics; visual analytics tools; visualization;
fLanguage :
English
Journal_Title :
Computer Graphics and Applications, IEEE
Publisher :
ieee
ISSN :
0272-1716
Type :
jour
DOI :
10.1109/MCG.2015.64
Filename :
7111924
Link To Document :
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