Florida Museum of Natural History

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IMPLEMENTING LINNE

Implementation of LINNE will:

  1. Modernize infrastructure for taxonomic research.
    Advances in cyberinfrastructure and information technology that increase efficiency must be made available to centers of taxonomic research. Roughly one billion biological specimens are curated in museums worldwide, and each specimen often contributes to many datasets. Researchers working with collections will be provided access through the LINNE network to technology that provides for high-bandwidth image and data capture, online workbenches for identification, georeferencing, data analysis and visualization, and electronic publication. This technology includes digital imaging resources such as remote-controlled digital microscopes, high resolution 2D and 3D surface and deep tissue imaging through computed tomography (CT scanning) and magnetic resonance imaging (MRI), high-throughput DNA sequencing facilities, and digital libraries that place 250 years of published and archived information at our fingertips. Tens of millions of specimen records are now available through electronic resources such as the Global Biodiversity Information Facility (GBIF). Although only the tip of the iceberg, this access to data held in hundreds of institutions from a single portal demonstrates how technology can transform modern taxonomy. With LINNE, comprehensive data capture, analysis, and electronic publication will be available to all researchers via cyberinfrastructure that will provide transparent data access for billions of records across a network of hundreds of institutions.

  2. Enhance the nation's taxonomic workforce.
    future workforce Taxonomy is labor-intensive and requires specialized scholars. A new generation of taxonomists must be educated and supported to explore and document the world's species. NSF's PEET (Partnerships for Enhancing Expertise in Taxonomy) program must be expanded, and other means of educating students and fostering interest in taxonomy must be identified and supported. In addition to accelerating the training of taxonomists, LINNE will foster collaborations to realize the full potential of the taxonomic community. Institutions of all sizes, educators at all levels, and the general public will have the opportunity to contribute to and benefit from taxonomic research.

  3. Modernize collection facilities.
    Specimens harbor much more data than can be captured or displayed electronically. It is vital to recognize the source of information — the specimens themselves — and to guarantee their availability to future generations. LINNE will provide improvements in collection facilities, from environmentally controlled buildings to archival tissue storage, and provide the technical assistance necessary to properly manage collections.

  4. Update and verify specimen indentifications.
    Accurate identification of specimens in collections is necessary for research on the spatial and temporal distributions of organisms. Many specimens in collections now are unidentified or incorrectly identified (estimates of misidentified specimens for particular taxonomic groups range from 10 to 70%). LINNE will increase the pace of taxonomic revisions (in part by supporting an expansion of NSF's Revisionary Syntheses in Systematics initiative), provide new tools for specimen identification, and ensure that the information content of collections is accurate and electronically accessible.

  5. Establish linkages at multiple levels.
    LINNE will transform how taxonomy is done and used through innovative linkages at multiple levels. Teams of taxonomists will be linked with each other and research resources to expedite revisions, monographs, and inventories. Natural history collections will be linked across the nation to form the backbone of LINNE and make new kinds of research possible. Taxonomic information will be linked to diverse sources of information from many fields to address environmental challenges. LINNE will support and benefit from linkages to a wide range of activities in ecology, ecosystem science, bioinformatics, information sciences, geology, land planning, and resource management, including NEON (National Ecological Observatory Network), GBIF (Global Biodiversity Information Facility), CHRONOS (an Interactive Network of Data and Tools for Earth System History), and TDWG (Taxonomic Databases Working Group).

implementation phases

ONLINE IDENTIFICATIONS

Compiling the knowledge for identifying the known 1.75 million different species on Earth is an enormous task. Identification keys and manuals traditionally have been printed; although computer identification tools have been around since the late 1960s, they have not been widely utilized. LINNE will provide the infrastructure needed to build online identification facilities such as the Electronic Field Guide (EFG), and SPIDA-web.

Electronic Field Guide (EFG), developed at the University of Massachusetts, Boston, is a tool that allows researchers to build their own online keys from observations, measurements, images, and publications. As explained on the EFG Web site, EFG "aims to provide a database management system for manipulating taxonomic information associated with the tree of life based on Linnaeus' model. It is intended for use as an educational research tool to assist users in accessing data regarding taxa. It will help biology researchers to identify species by performing iterative classification through elaboration of characteristics."

An Internet-accessible automated identification system that uses neural networks to make species identifications based on digital images is under development at the American Museum of Natural History. The goal is to create a system that can identify species without requiring the user to have more than the most basic knowledge of the organisms to be identified. The prototype, "SPIDA-web" (SPecies IDentification, Automated, web accessible), will identify images of spiders submitted via a Web page and provide distributional and other information from a database. Internet-accessible automated identification systems have the potential to facilitate studies of diverse taxa and to lead to an explosion of knowledge about our biodiversity.


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