The BioGeomancer project team at the Peabody Museum of Natural History is developing a universal system for geo-referencing of the diverse specimen records that exist in natural history collections using software licensed from Inxight Software Inc.
BioGeomancer is a research consortium of seven academic institutions that is coordinated by the University of California at Berkeley. The consortium will feature an online workbench and online services to provide geo-referencing for collectors, curators and users of natural history specimens.
Reed Beaman, associate director of the Informatics Program at the Peabody , will lead Yale's team in developing software tools to allow easy conversion of archival data records that were collected in many different formats into a standardized form.
Over the past 250 years, biologists have gone into the field to collect specimens and associated environmental information documenting the range of life. This archive of Earth's biological diversity plays a fundamental role in generating new knowledge and guiding conservation decisions. Yet, roughly one billion specimen records, and even more species observation records, remain practically unusable in their current form, explains Beaman.
"The greatest challenge to the effective use of this continuously growing archive is geo-referencing, or converting the text descriptions of places where data and specimens were collected -- locality descriptions such as 'North Beach, Point Reyes, Marin County, California' -- into formal geospatial coordinate systems that can be mapped," says Beaman. "The number of unreferenced records has been overwhelming, and severely limits the effective analysis of past and current species distributions."
The system Beaman's team is developing, using Inxight's SmartDiscovery™ Fact Extraction module, will be able to process thousands of sample entries in a few minutes, expanding the information that can mesh with data from other disciplines (climatology, geology, human impacts, etc.) for biodiversity conservation.
The Fact Extraction software can identify and extract items, events, activities and relationships from text data sources like specimen labels. Consortium users will be able to obtain relationships and facts of interest from search results; identify relationships between subjects that are not obvious; and track trends over time or by location.
The project is funded by the Gordon and Betty Moore Foundation, which supports initiatives tackling complex challenges in the areas of environmental conservation, science, higher education and the San Francisco Bay Area.
-- By Janet Emanuel
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