This is an excerpt from an article by SDSC science writer Paul Tooby that originally appeared in the NPACI publication “Envision” April-June 2003 (http://www.npaci.edu/envision/v19.2/seek.html)
Researchers working on the National Science Foundation (NSF)-sponsored Science Environment for Ecological Knowledge (SEEK) are building a powerful information infrastructure that will offer a unique capabilities for research and synthesis.
SEEK is an ambitious five-year NSF Information Technology Research project that will access, model, synthesize and display ecological data across ecosystems and spatial and temporal scales, facilitating investigations involving all of the physical and life sciences.
"It’s a lot of work to build a comprehensive system like SEEK, but it’s the key to being able to achieve an overall understanding of ecological systems," says Bill Michener, principal investigator. "All the parts an ecosystem are connected, and to understand them you need to encompass all the components in your model."
SEEK will also provide researchers with analysis and visualization capabilities, freeing them from needing specialized IT knowledge, and offering a powerful platform to do science much more rapidly and on a larger scale than possible before.
SEEK is an outgrowth of ecological and biodiversity informatics research and includes computer scientists, ecologists, and technologists. The lead organizations involved are part of the Partnership for Biodiversity Informatics, a consortium made up of the National Center for Ecological Analysis and Synthesis (NCEAS) at UC Santa Barbara; the San Diego Supercomputer Center (SDSC) and UC San Diego; the Natural History Museum and Biodiversity Research Center at the University of Kansas (KU); and the LTER Network Office at the University of New Mexico. Additional partnering institutions are Arizona State University, the University of North Carolina, the University of Vermont, and Napier University in Scotland.
The researcher uses the SEEK interface to identify data sets containing observations such as temperature, rainfall, and soil type. SEEK then pulls in specimen databases that also have locality information. Initially, SEEK will include sources such as the Species Analyst at KU, which accesses museum databases, the MetaCat catalog from the Knowledge Network for Biocomplexity (NCEAS, LTER, etc.), and other ecological data sources (see LTER NETWORK NEWS - Fall 2000 http://news.lternet.edu/article%5Bfield_story_id-id%5D.html-124).
"The trick is that all the data layers have to be integrated using the same cell size and spatial extent, taking into consideration the effects that scaling and other transformations might have on an analysis," say Matt Jones, SEEK project manager and a researcher at NCEAS. "SEEK will then transform them so that they’re all at the same scale." Once the data is available in SEEK, it is pushed into the ecological niche model, which may be running elsewhere on a different machine. The results are then overlaid onto a map of the study area, producing a graphic that highlights information vital to the project.
"An important feature of SEEK is that it goes beyond providing data integration and analysis services," Jones says. The output from the ecological niche model may turn out to be useful also for other apparently unrelated processes. In this way, SEEK can become “smarter" with use, “leading eventually to vastly expanded virtual collaborations that could eventually become community-wide,” says David Vieglais, a research scientist at the Natural History Museum and Biodiversity Research Center at the University of Kansas.
In order for SEEK to work, scientists will need to adopt common protocols for gathering and recording data, and will need to use common “metadata,” the information that describes their data. These and other changes will take some adjustment in the research community, says Michener, who will host workshops and other outreach activities to initiate and train growing numbers of ecologists about the benefits of doing ecology in this new way.