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Lifemapper 2.0

Lifemapper 2.0. Using and Creating Geospatial Data and Open Source Tools for the Biological Community. Aimee Stewart, CJ Grady, Dave Vieglais, Jim Beach Natural History Museum and Biodiversity Institute University of Kansas. Overview. Overall Goals History Current version

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Lifemapper 2.0

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  1. Lifemapper 2.0 Using and Creating Geospatial Data and Open Source Tools for the Biological Community Aimee Stewart, CJ Grady, Dave Vieglais, Jim Beach Natural History Museum and Biodiversity Institute University of Kansas

  2. Overview • Overall Goals • History • Current version • Implementation • Future

  3. Niche Modeling • Yeah yeah yeah • Data • Environmental • Occurrence • Computationallimitations

  4. Lifemapper 1.0 • NSF funded • Experimental app. • Successful DC project • Enthusiastic users • Limited by • Data quality • Architectural decisions

  5. Lifemapper 2.0 • Demo pipeline processing specimen data from GBIF cache • Funded by NSF/EPSCoR • Simpler, controlled architecture • Goals • On demand computation • Model archive • Data and analysis service

  6. Components • Cluster • Spatial datalibrary (SDL) • Workflow controller • Open-source • Python

  7. Operation • Client • retrieves point data • constructs request • sends job to cluster by REST • Cluster front end receives /schedules job • Cluster nodes • retrieve environmental data • dispatch job to OM • Client • polls for status • retrieves and stores model/projection

  8. Data • Environmental data • URL in job, retrieved via WCS by node • Caches on nodes for efficiency • Point data • Could be REST or WFS URL • Result data • Model (ruleset) stored on file system • Projection (raster map) registered in SDL

  9. Cluster • 64 node, 128 processors • 2 TB storage • NPACI Rocks • Sun Grid Engine scheduler • HTTP REST service • Run openModeller (GARP or other algorithm) • Get status • Get result data

  10. Spatial Data Library • Mapserver with custom python W*S • Layer metadata in PostGIS • Independent service - so could • be standalone • be one of multiple SDLs servicing pipeline • Will have • search/query webservice • browsable web interface

  11. Workflow Controller • Could simply generate jobs … so easy to integrate • Currently • Harvests from GBIF • Generates jobs per species • Reproduce LM1 but with refined data and scalable system

  12. Overall system • Standalone system • Only outside connection is REST service • Easily moved to smaller/larger system • Or multiple systems for failover for high demand • Interface - easier than existing SOAP • Designed to provide high throughput, not rapid evaluation of single model • Open Source Software

  13. Implementation Status • Core components operational • harvest data • generate jobs • output projections • store back to SDL • No user interface yet • W*S so existing viz solutions easy

  14. What does the future hold? • Fine-tune • Taxonomicresolution • Data cleaning • Multiple • algorithms • projection scenarios • Analysis services

  15. Acknowledgements • Funding • NSF Award (EPSCoR 0553722) • Kansas Technology Enterprise Corporation • openModeller • CRIA and more • Original GARP • David Stockwell, SDSC • Environmental data • Climate Research Unit • Int. Panel on Climate change • Normalization BDWorld, Tim Sutton, Pete Brewer • GBIF and contributing collections • Lifemapper1 Team, especially Ricardo Pereira

  16. Questions?

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