Reducing the Analytical Bottleneck for Domain Scientists: Lessons from a Climate Data Visualization Case Study

Journal Article · Thu Dec 31 23:00:00 EST 2015 · Computing in Science and Engineering

DOI:https://doi.org/10.1109/MCSE.2016.7· OSTI ID:1255368

Dasgupta, Aritra; Poco, Jorge; Bertini, Enrico; Silva, Claudio T.

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, etc. 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 paper, by reflecting on a set of successful collaborative research efforts between with a group of climate scientists and visualization researchers, we introspect how interactive visualization can help reduce the analytical bottleneck for domain scientists.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1255368
• Report Number(s): PNNL-SA-114816
• Journal Information: Computing in Science and Engineering, Journal Name: Computing in Science and Engineering Journal Issue: 1 Vol. 18; ISSN 1521-9615
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

climate
visual analytics