VISTAS, funded by the National Science Foundation
(CISE/CNS-CPS 1637320 and BIO/DBI 1062572 )
and joint among scientists at The Evergreen State College, Oregon State University, and elsewhere, develops visual analytics software to enable scientists to better understand and communicate about large and complex environmental problems that span spatial and temporal scales.
Read more about and download VISTAS software at VISTAS-software page.
Look at VISTAS example images created by Environmental Scientists.
Below, we briefly describe the VISTAS project, here is our original 2010 NSF proposal (15 p), and the NSF panel reviews.
Our research suggests VISTAS will help scientists understand relationships among ecological processes at the same and different scales, develop new testable hypotheses, and explain research results. The project has three objectives:
- Conduct Ecology Informatics research to enable the required visual analytics and implement a proof of concept software tool: VISualization of Terrestrial-Aquatic Systems (VISTAS).
- Co-develop VISTAS with environmental scientists who will use VISTAS in studies spanning spatial and temporal scales.
- Apply social science methods to study the co-development and usability of VISTAS and its visual analytics.
We also convene a six-member panel, The Northwest Computer Science Consortium to Enhance the Study of Climate Change, which will advise VISTAS scientists and developers, and enlist the CS research community in R&D applicable to environmental science.
In this Petabyte Age, digital information increases at a prodigious rate – much of it due to new environmental monitoring such as remote sensing and national environmental observatories, research networks such as NSF’s Long Term Ecological Research program, and meteorological stations. Increasingly, scientists use such massive data sets to make and test hypotheses and predict natural phenomena.
The sheer amount of data presents challenges, although this data deluge is only one complicating factor: The most critical environmental science problems – including climate change, invasive species, species diversity, ecosystem functioning, and infectious diseases – have complex, highly distributed, and heterogeneous data that span time and spatial scales. Because analytical methods to transcend these scales are not well understood, this project is designed to determine whether visualizing natural phenomena in new ways can help scientists develop intuition and hypotheses at multiple scales – improving their ability to formulate new insights about ecosystem services, and patterns and processes, in complex environmental systems. As important, visualizations also help scientists communicate these insights to non-scientists.
If successful, the project’s greatest impact will be in environmental science research – enabling scientists to better understand and communicate complex processes at multiple spatial scales. A long-term vision includes improving evidence-based practice of natural resource management with visual analytics. The project takes seriously obligations to assure dissemination, technology transfer and sustainability of research results and tool development, so other impacts include:
- Technology transfer of results beyond normal dissemination channels (scholarly publication and presentation), i.e., communication of results to natural resource managers and policy makers, producers of scientific software, information managers serving scientists, and computer scientists (thus encouraging basic research in areas that would benefit scientific software development and lead to new technology useful in science and beyond).
- Presentation of our scientists’ use of VISTAS to natural resource managers and policy makers, and to professional master’s students.
- Involving undergraduate and graduate students in research, and enhancing environmental science and computer science education at our institutions with materials from this work.
- Continuation of past successful dissemination of interdisciplinary educational materials and integration of visualizations from this work into an existing program for middle school girls.