Welcome

Advancing Cyberinfrastructure-Based Science through Education, Training, and Mentoring of Science Communities

This project is dedicated to assisting scientists in the design of technology-enabled science, particularly ecologists, environmental scientists, and other earth surface/biosphere scientists. It is funded by the National Science Foundation (NSF) Office of Cyberinfrastructure through the CI-Team program. This was originally a one-year demonstration project to show the efficacy of the approach. It received continued funding as a three-year implementation project.

The project is being conducted through the University of New Mexico Center for Research on Ecological Science and Technology (CREST) in collaboration with the UNM High Performance Computing Center, the UNM Center for Rapid Environmental Assessment & Terrain Evaluation, the University of Arizona Department of Geography and Regional Development, Northern Arizona University Merriam-Powell Center for Environmental Research, and University of Kansas Biodiversity and Natural History Museum.

Publications

Hear an interview with Deana Pennington on the blog radio show "Tom Cox on Leadership" on the topic of alignment across silos

In progress:

Pennington, D., (under revision), Enabling co-emergent innovation in collaborative science and technology research teams: A distributed cognition approach.

Pennington, D., (submitted), The dynamics of material artifacts in collaborative research teams.

Accepted, in press, or published:

Pennington, D., (in press), Conceptual improvisation: Generating co-created research problems in eScience teams. Computer Supported Cooperative Work Special Issue on Embedding eResearch Applications: Project Management and Usability

Pennington, D. (in press), Enabling science and technology research teams: A breadmaking metaphor, Educause Quarterly.

Downey, L.L. and Pennington, D., (2009), Bridging the gap between technology and science with examples from ecology and biodiversity. International Journal of Biodiversity Informatics [online]

Pennington, D., Athanasiadis, I.N., Bowers, S., Krivov, S., Madin, J., Schildhauer, M., and Villa, F., (2009), Indirectly-driven knowledge modeling in ecology. International Journal of Metadata, Semantics and Ontologies 3(3):210-225.

Tools

This is a list of potentially relevant tools.

    Spatially-explicit collective raster analysis

  • z-scores
    Spatiotemporal analysis of multiple rasters