A SCALED RELATIONAL DATABASE DESIGN FOR ORGANIZING AND ANALYZING INFORMATION: APPLICATION TO GEOLOGY AND ORE DEPOSITS OF THE GREAT BASIN

Geoscientists with the U.S. Geological Survey's Metallogeny of the Great Basin Project are developing a comprehensive relational database to manage large volumes of existing and newly compiled data to facilitate understanding of relationships between world-class ore deposits and associated geologic features in the Great Basin. Scientists routinely synthesize attributes of geologic features to solve earth science problems. A growing and challenging technical concern is how to develop user-friendly, computer-aided schemes to store, organize, update, and analyze data pertinent to these problems. Project geologist’s are exploring the utility of a scaled, relational database to manage increasing volumes of diverse data. Geologic information ranging from mineral isotopic data to regional mapping is acquired from regions containing gold and base-metal deposits, industrial mineral deposits, geothermal resources, petroleum reserves, and non-mineralized terrain and then recorded as feature attributes. For example, mineral resource information is organized in the telescoping hierarchy scheme: sample, ore deposit, hydrothermal system, mineral belt, and metallogenic province. This "scale of observation" organization links sample-sized attributes, which populate a database, to a family of increasingly larger-scale feature attributes at higher levels in the database. Relational database keys (join-items) merge data across this heirarchy scheme to permit further relavent queries. Relational join-items cross-link to analogous sedimentary rocks, igneous rocks and deformational features datasets each of which are linked to isotopic and fossil age data to facilitate understanding of the temporal, spatial, and genetic relationship of ore deposits to other geologic features. This scheme enables users to retreive pertinent information from multiple datasets for input into external software for various GIS, statistical, petrologic, or other analyses. The results of these analyses are used to populate additional database fields. This relational database is both a conventional data storage, organization and retrieval system and a research tool that allows scientists to efficiently work with information in creative ways to solve geologic problems.