SEEK project works to create cyberinfrastructure prototype using LTER grassland biodiversity and production data.
The LTER Network has long recognized the importance of developing a broad-scale understanding of biodiversity processes and how altered biodiversity affects ecosystem response. The need to synthesize an ever-increasing body of biodiversity and productivity data is essential toward that end. Past synthetic studies of species diversity and productivity relationships (Waide et al. 1999; Gross et al. 2000; Scheiner et al. 2000; Knapp & Smith 2001; Knapp et al. 2004) have largely been accomplished by manually integrating many data sets-a lengthy and tedious process at best. Given the network-wide emphasis on synthetic, cross-site studies and the voluminous data anticipated from the National Ecological Observatory Network (NEON) project, the need for automated methods of integrating heterogeneous data for use in sophisticated analyses is paramount.
SEEK http://seek.ecoinformatics.org is a large, NSF-funded Information Technology Research (ITR) project designed to provide solutions for data integration (Michener et al. accepted). The SEEK cyberinfrastructure is currently being prototyped and tested with biodiversity and productivity data from six LTER grassland sites (ARC, GCE, JRN, KBS, NWT, and SGS) through a collaborative working group. The group includes ecologists and information managers associated with the participating sites, geospatial scientists, ecoinformatics specialists, computer scientists, and software developers from the LTER Network Office, National Center for Ecological Analysis and Synthesis, and University of California, Davis. The goal of the prototype project is to design generic tools for automated or semi-automated data integration based on the specific characteristics of these data sets. The robustness of the tools will be tested on data from additional sites. The integrated datasets will then be input into the Kepler Workflow System http://www.kepler-project.org, which provides automated analysis and modeling.
The SEEK project builds on prior research on ecological metadata standards http://knb.ecoinformatics.org. This prototype project requires level 5 metadata (the most detailed level) and will demonstrate the effectiveness of metadata-driven approaches to data discovery, integration, and analysis in ecology. A second prototype project is developing computer-intensive approaches, using broad-scale species distribution analysis with ecological niche modeling (Peterson & Vieglais, 2001). Both prototypes will benefit from cutting-edge IT approaches in ontologies and semantic mediation that formally capture the knowledge of a discipline for logical reasoning by the system.
Such approaches (data-intensive, computer-intensive, and discipline-intensive) are being researched across many scientific communities in ongoing projects and represent an emerging scientific cyberinfrastructure framework. The SEEK project, which makes use of all of these new approaches, is the forerunner of cyberinfrastructure design for the NEON project, which will implement the design for synthetic research across all scientific questions of interest.
References
Gross, K. L., M. R. Willig, L. Gough, R. Inouye and S. B. Cox (2000). Patterns of species density and productivity at different spatial scales in herbaceous plant communities. Oikos, 89, 417-427.
Knapp, A. K. and M. D. Smith (2001). Variation among biomes in temporal dynamics of aboveground primary production. Science, 291, 481-484.
Knapp, A. K., M. D. Smith, S. L. Collins, N. Zambatis, M. Peel, S. Emery, J. Wojdak, M. C. Horner-Devine, H. Biggs, J. Kruger and S. J. Andelman (2004). Generality in ecology: testing North American grassland rules in South African savannas. Frontiers in Ecology and the Environment, 2, 483-491.
Michener, W. K., J. H. Beach, M. B. Jones, B. Ludaescher, D. Pennington, R. S. Pereira, A. Rajasekar and M. Schildhauer (accepted). A knowledge environment for the biodiversity and ecological sciences. Journal of Intelligent Information Systems.
Peterson, A. T. and D. A. Vieglais (2001). Predicting species invasions using ecological niche modeling: new approaches from bioinformatics attack a pressing problem. BioScience, 51, 363-371.
Scheiner, S. M., S. B. Cox, M. Willig, G. G. Mittelbach, C. Osenberg and M. Kaspari (2000). Species richness, species-area curves and Simpson's paradox. Evolutionary Ecology Research, 2, 791-802.
Waide, R. B., M. R. Willig, C. F. Steiner, G. Mittelbach, L. Gough, S. I. Dodson, G. P. Juday and R. Parmenter (1999). The relationship between productivity and species richness. Annual Review of Ecology and Systematics, 30, 257-300.
Deana D. Pennington
SEEK Project, LNO