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Abstract Detail

Biodiversity Informatics & Herbarium Digitization

Harbert, Robert S [1].

Efficient data mining of global primary biodiversity data using SQL database mirrors.

Biodiversity data available online through the Global Biodiversity Information Facility (GBIF) and others (e.g., Biodiversity Information Serving Our Nation — BISON, and iNaturalist) are growing every day as more data are mobilized and/or collected. For large-scale projects involving data for thousands of taxa and millions of individual observations, one bottle-neck for computation is data access and reproducibility. In an attempt to resolve the access problem we present a road-map for the democratization of big-biodiversity-data through distributed or local mirrors of large biodiversity databases that make use of SQL storage architecture and efficient database search algorithms to provide up-to-date and rapid access to biodiversity data. Performance gains under this model will be presented and prospective work leveraging data at scales appropriate for this approach will be discussed in the context of stacked distribution models for assessment of plant biodiversity.

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1 - American Museum of Natural History, Sackler Institute for Comparative Genomics, Central Park West & 79th St., New York, NY, 10024, United States

ecological niche modeling
Digital Data

Presentation Type: Oral Paper
Session: 31, Biodiversity Informatics & Herbarium Digitization I
Location: Fort Worth Ballroom 6/Omni Hotel
Date: Tuesday, June 27th, 2017
Time: 3:00 PM
Number: 31005
Abstract ID:286
Candidate for Awards:None

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