The Community for Technology Leaders
2008 IEEE Fourth International Conference on eScience (2008)
Indianapolis, IN
Dec. 7, 2008 to Dec. 12, 2008
ISBN: 978-1-4244-3380-3
pp: 368-369
ABSTRACT
Scientific fields of study such as astrobiology and cave and karst science contain large collections of images and their associated biological, physiochemical, and geological datasets. The vast majority of these images are never shared or examined by more than a handful of scientists. Being able to mine these kinds of data to make new linkages and discoveries becomes ever more important as interdisciplinary studies grow in importance. The goal of our project is to design and implement an online workspace to allow scientists to collaboratively view, analyze, and annotate visual datasets and to train future scientists in the power of collaborative workspaces. We are creating a series of electronic scenarios that address unresolved questions in geomicrobiology, such as the question of which materials are biological in origin. These questions have important implications for the detection of life on other planets and in our subterranean worlds of caves. Our initial albums focus on the geomicrobiology of caves and karst. The target users are the interdisciplinary community of scientists who study karst samples to learn more about critical biological and geological processes and the microbial communities often found in karst terrain. Our pilot project of such a collaborative workspace is IDEC: Imagery Data Extraction Collaborative, created by our group, that consists of an integration of three open-source tools: Drupal, Gallery, and DSpace. We are using this configuration as a base for developing our broader collaborative workspaces for knowledge discovery with weblogs, forums, feeds, and image functionality enabled.
INDEX TERMS
data mining, image recognition, knowledge discovery, karst
CITATION
Diana E. Northup, Christy Crowley, James E. Powell, Johann van Reenen, Linn Marks Collins, M. Alex Baker, Brian Freels-Stendel, Mark L. B. Martinez, "Imagery Data Mining: The IDEC Experiment", 2008 IEEE Fourth International Conference on eScience, vol. 00, no. , pp. 368-369, 2008, doi:10.1109/eScience.2008.133
92 ms
(Ver 3.3 (11022016))