(In?)Extricable Links between Data and Visualization: Preliminary Results from the VISTAS Project
Our initial survey of visualization tools for environmental science applications iden-tified sophisticated tools such as The Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers (VAPOR) [http://www.vapor.ucar.edu], and Man computer Interactive Data Access System (McIDAS)andThe Integrated Data Viewer (IDV) [http://www.unidata.ucar.edu/software]. A second survey of ours (32,279 figures in 1,298 articles published between July and December 2011 in 9 environmental science (ES) journals) suggests a gap between extant visualization tools and what scientists actually use; the vast majority of published ES visualizations are statistical graphs, presenting evidence to colleagues in respective subdisciplines. Based on informal, qualitative interviews with collaborators, and communication with scientists at conferences such as AGU and ESA, we hypothesize that visualizations of natural phenomena that differ significantly from what we found in the journals would positively impact scientists’ ability to tune models, intuit testable hypotheses, and communicate results. If using more sophisticated visualizations is potentially so desirable, why don’t environmental scientists use the available tools?
KeywordsEnvironmental Science Environmental Scientist Visualization Software Scientific Visualization Multiple Ecosystem Service
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- 1.Cushing, J.B., et al.: What you see is what you get? In: Data Visualization Options for Environmental Scientists. Ecological Informatics Management Conference (2011)Google Scholar
- 2.Schultz, N., Bailey, M.: Using extruded volumes to visualize time-series datasets. In: Dill, J., et al. (eds.) Expanding the Frontiers of Visual Analytics and Visualization, pp. 127–148. Springer (2012) ISBN 978-1-4471-2803-8Google Scholar
- 3.Alexander, F., et al.: Big Data. IEEE Computing in Science & Engineering 13, 10–13 (2011)Google Scholar
- 4.Maier, D.: Navigating Oceans of Data. In: Abstracts of the Conference on Scientific and Statistical Database Management, http://cgi.di.uoa.gr/~ssdbm12/keynote1.html
- 6.Smelik, R.M., et al.: Survey of Procedural Methods for Terrain Modeling. In: Egges, A., et al. (eds.) Proc. of the CASA Workshop on 3D Advanced Media in Gaming and Simulation (3AMIGAS), Amsterdam, The Netherlands, pp. 25–24 (2009)Google Scholar
- 9.McKane, R., et al.: Integrated eco-hydrologic modeling framework for assessing effects of interacting stressors on multiple ecosystem services. ESA Annual Meeting (August 2010) Google Scholar