Challenges in Visual Data Analysis

In today's applications data is produced at unprecedented rates. While the capacity to collect and store new data grows rapidly, the ability to analyze these data volumes increases at much lower pace. This gap leads to new challenges in the analysis process, since analysts, decision makers, eng...

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Bibliographic Details
Main Authors: Keim, D.A., Mansmann, F., Schneidewind, J., Ziegler, H.
Format: Conference Proceeding
Language:English
Subjects:
Application software
Data analysis
Data engineering
Data mining
Data visualization
Humans
Information analysis
Space exploration
Statistical analysis
Visual analytics
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Summary:In today's applications data is produced at unprecedented rates. While the capacity to collect and store new data grows rapidly, the ability to analyze these data volumes increases at much lower pace. This gap leads to new challenges in the analysis process, since analysts, decision makers, engineers, or emergency response teams depend on information "concealed" in the data. The emerging field of visual analytics focuses on handling massive, heterogenous, and dynamic volumes of information through integration of human judgement by means of visual representations and interaction techniques in the analysis process. Furthermore, it is the combination of related research areas including visualization, data mining, and statistics that turns visual analytics into a promising field of research. This paper aims at providing an overview of visual analytics, its scope and concepts, and details the most important technical research challenges in the field
ISSN:1550-6037
2375-0138
DOI:10.1109/IV.2006.31