2008 Joint Meeting of The Geological Society of America, Soil Science Society of America, American Society of Agronomy, Crop Science Society of America, Gulf Coast Association of Geological Societies with the Gulf Coast Section of SEPM

Paper No. 6
Presentation Time: 8:00 AM-4:45 PM

Geoscience Data Portals – Recommendation Systems Built from Monitoring Usage Patterns

CROSBY, Christopher J.1, NANDIGAM, Viswanath1 and BARU, Chaitan2, (1)San Diego Supercomputer Center, University of California, San Diego, MC 0505, 9500 Gilman Drive, La Jolla, CA 92093-0505, (2)San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Dr. #0505, La Jolla, CA 92093, ccrosby@sdsc.edu

Since its inception four years ago, the GEON Project (portalwww.geongrid.org) has been providing access to a variety of geoscience datasets such as geologic maps, paleontologic databases, gravity and magnetics data and LiDAR topography via its online portal interface. In addition to data, the GEON Portal also provides web-based tools and other resources that enable users to process and interact with data. By taking advantage of the portal framework, user access patterns and behavior can be recorded. This information includes the datasets being accessed, types of processing commonly used along with other usage patterns. This record of usage patterns is a rich resource for exploring how earth scientists discover and utilize internet-based datasets and could ultimately be harnessed to optimize how users interact with the data portal. The paradigm of integrating popular and commonly used patterns to make recommendations to a user is well established in the world of e-commerce where users receive suggestions on books, music and other products that they may find interesting based on their website browsing and purchasing history. This paradigm has not yet been explored for geoscience data portals. We will present an initial analysis of user access and processing statistics for the GEON LiDAR topography system to illustrate what the statistics reveal about user's spatial and temporal data access patterns, data processing parameter selections, and pathways through the data portal. We also demonstrate what these usage statistics can illustrate about aspects of the datasets that are of greatest interest. Finally, we explore how these usage statistics could be used to improve the user's experience in the data portal and to optimize how data access interfaces and tools are designed and implemented.