HR: 1340h
AN: H13H-1684    [Abstracts]
TI: OLAP Cube Visualization of Hydrologic Data Catalogs
AU: Zaslavsky, I
EM: zaslavsk@sdsc.edu
AF: San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093- 0505, United States
AU: Rodriguez, M
EM: MKRodriguez@lbl.gov
AF: San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093- 0505, United States
AU: Beran, B
EM: bora.beran@gmail.com
AF: Microsoft Research, 455 Market St., Suite 1690, San Francisco, CA 94105, United States
AU: Valentine, D
EM: valentin@sdsc.edu
AF: San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093- 0505, United States
AU: * van Ingen, C
EM: vaningen@windows.microsoft.com
AF: Microsoft Research, 455 Market St., Suite 1690, San Francisco, CA 94105, United States
AU: Wallis, J C
EM: jwallisi@ucla.edu
AF: Center for Embedded Networked Sensing, University of California, Los Angeles, Los Angeles, CA 90095-1596, United States
AB: As part of the CUAHSI Hydrologic Information System project, we assemble comprehensive observations data catalogs that support CUAHSI data discovery services (WaterOneFlow services) and online mapping interfaces (e.g. the Data Access System for Hydrology, DASH). These catalogs describe several nation-wide data repositories that are important for hydrologists, including USGS NWIS and EPA STORET data collections. The catalogs contain a wealth of information reflecting the entire history and geography of hydrologic observations in the US. Managing such catalogs requires high performance analysis and visualization technologies. OLAP (Online Analytical Processing) cube, often called data cubes, is an approach to organizing and querying large multi-dimensional data collections. We have applied the OLAP techniques, as implemented in Microsoft SQL Server 2005, to the analysis of the catalogs from several agencies. In this initial report, we focus on the OLAP technology as applied to catalogs, and preliminary results of the analysis. Specifically, we describe the challenges of generating OLAP cube dimensions, and defining aggregations and views for data catalogs as opposed to observations data themselves. The initial results are related to hydrologic data availability from the observations data catalogs. The results reflect geography and history of available data totals from USGS NWIS and EPA STORET repositories, and spatial and temporal dynamics of available measurements for several key nutrient-related parameters.
DE: 1805 Computational hydrology
DE: 1819 Geographic Information Systems (GIS)
DE: 6339 System design
SC: Hydrology [H]
MN: 2007 Fall Meeting