Title
Reducing the Analytical Bottleneck for Domain Scientists: Lessons from a Climate Data Visualization Case Study
Date Issued
01 January 2016
Access level
metadata only access
Resource Type
review
Author(s)
Dasgupta A.
Bertini E.
Silva C.T.
University of Washington
Publisher(s)
IEEE Computer Society
Abstract
The gap between large-scale data production rate and the rate of generation of data-driven scientific insights has led to an analytical bottleneck in scientific domains like climate, biology, and so on. This is primarily due to the lack of innovative analytical tools that can help scientists efficiently analyze and explore alternative hypotheses about the data and communicate their findings effectively to a broad audience. In this article, by reflecting on a set of successful collaborative research efforts between with a group of climate scientists and visualization researchers, the authors introspect how interactive visualization can help reduce the analytical bottleneck for domain scientists.
Start page
92
End page
100
Volume
18
Issue
1
Language
English
OCDE Knowledge area
Meteorología y ciencias atmosféricas Ciencias del medio ambiente
Scopus EID
2-s2.0-84961695949
Source
Computing in Science and Engineering
ISSN of the container
15219615
Sponsor(s)
National Science Foundation -1229185 NSF
Sources of information: Directorio de Producción Científica Scopus