Biodiversity Data Retrieval and Integration Distributed species, data, computation and credit

1. Biodiversity Data Retrieval and IntegrationDistributed species, data, computation and credit James H. Beach Biodiversity Research Center University of Kansas beach@ku.edu SINE Workshop, 29-31 Oct 2001, SDSC

2. Museums and their Data • 3 B specimens – and data – documenting the distribution of life on earth • 2 M species • 300 years of biological exploration • Data are held in dynamic, autonomous, self-organizing and spatially-distributed collections SINE Workshop, 29-31 Oct 2001, SDSC

3. Paris Museum Mexican Birds SINE Workshop, 29-31 Oct 2001, SDSC

4. British Museum Mexican Birds SINE Workshop, 29-31 Oct 2001, SDSC

5. Field Museum Mexican Birds SINE Workshop, 29-31 Oct 2001, SDSC

6. KU Museum Mexican Birds SINE Workshop, 29-31 Oct 2001, SDSC

7. “World Museum” Mexican Birds SINE Workshop, 29-31 Oct 2001, SDSC

8. DesktopApplications ClientAPI The Species Analyst Network • Direct access to live primary data • Ownership and control maintained locally • Z39.50, HTTP, XML data, XML Query Broadcast query Data Resources SINE Workshop, 29-31 Oct 2001, SDSC

9. Species Analyst HTML Gateway SINE Workshop, 29-31 Oct 2001, SDSC

10. Results of Species Analyst Query SINE Workshop, 29-31 Oct 2001, SDSC

11. GARP: Genetic Algorithm for Rule-set Production • Developed by David Stockwell, San Diego Supercomputer Center • Takes advantage of multiple algorithms (BIOCLIM, logistic regression, etc.) • Different decision rules may apply to different sectors of species’ distributions • Uses a genetic algorithm for choosing rules • Implemented on WWW, and open for public use SINE Workshop, 29-31 Oct 2001, SDSC

12. Species Analyst + GARP: A Powerful Tool • Integrates distributed biodiversity data • Provides current information on species’ ranges • Models species’ ecological niches • Predicts geographic distributions • Integrates niche models with environmental change scenarios, e.g. global climate change and biodiversity, invasive species, emerging diseases SINE Workshop, 29-31 Oct 2001, SDSC

13. Asian Longhorn Beetle (Anoplophora glabripennis) SINE Workshop, 29-31 Oct 2001, SDSC

14. Longhorn Beetle - Modeled Asian Distribution SINE Workshop, 29-31 Oct 2001, SDSC

15. Asian Longhorn Beetle – Predicted U.S. Distribution SINE Workshop, 29-31 Oct 2001, SDSC

16. A Global Encyclopedia of Life or The World According to GARP • Research • Biogeographic analysis on distributions • Invasive species predictions • Monitoring and conservation planning • Global climate change impacts on Biota • Outreach, Education and Training • Backyard biodiversity, spatial data queries, GIS functions • Interactive data entry, observational data • Data Analysis Services for Museums • Uniqueness and value of collections holdings • Data quality issues • Summary statistics and analyses SINE Workshop, 29-31 Oct 2001, SDSC

17. A Global Encyclopedia of Life or The World According to GARP (2) • Every documented species with georeferenced localities in the Species Analyst Network • North America, Western Hemisphere, World • Resolution 1 Km grid NA, 10 Km elsewhere • 1 M+ species in collections with data? • Computational Requirements SINE Workshop, 29-31 Oct 2001, SDSC

18. Metacomputing Museum Data • Global species distributions: parallel computation • SETI @ Home • Collaborative computing • 1 M simultaneous users • Port GARP to Win32 to run in background or foreground SINE Workshop, 29-31 Oct 2001, SDSC

19. Lifemapper = Georeferenced Species Data + Distributed Query Architecture + Predictive Modeling + Distributed Computation + Spatial Map and Model Archive + Open Access Web Portal SINE Workshop, 29-31 Oct 2001, SDSC

20. Lifemapper Demonstration • Server • GARP client SINE Workshop, 29-31 Oct 2001, SDSC

21. Lifemapper Future Directions Diversify modeling options, add interactivity, 3D analysis and visualization Add new classes of data layers, remote sensing, human impacts element, ecological models Add observational species data Embed dispersion models, temporal dimension Add internet services API, UDDI, SOAP Add more value-added services for data providers Embed LM data and analysis tools within a semantic research and decision support network Integrate LM into informal and formal science education

22. Lifemapper Social Scaling • Distributed authorship • Desktop computing • User preferences • Value-added collections data analysis • Acknowledgement and accreditation of contributions, ranks and statistics SINE Workshop, 29-31 Oct 2001, SDSC

23. Museums as Sensor Networks • Data are dynamic, servers & connections • Deborah Estrin -- Adaptive self-organization of the network, unattended and untethered -- parallels to curators and collection managers. • Self-assembling, observational data • Do not usually have the requirement of real time • Changes are as important • Source data (West Nile virus), model outputs • Frank Vernon mentioned that in many cases it is not the data values per se it is the change that is of importance • People as part of the Network • Doug Goodin people are part of the technological system” museum are sensors, they are observatories, but the latency of bringing the data into analysis engines is not measured in milliseconds but in field seasons, or decades to get formal publication of new scientific concepts. Many specimens and data are centuries old SINE Workshop, 29-31 Oct 2001, SDSC

24. Acknowledgements • University of Kansas • Dave Vieglais, Ricardo Pereira, Aimee Stewart, Greg Vorontsov, Town Peterson, BRC • SDSC • David Stockwell, Environmental Computing • University of Massachusetts-Boston • Bob Morris, CS, Rob Stevenson, Biology • UC Berkeley • John Wiecorek, Museum of Vertebrate Zoology • Dan Wertheimer, Space Science Laboratory • Agriculture Canada • Derek Munro, ITIS Canada Office • California Academy of Sciences • Stan Blum, Informatics SINE Workshop, 29-31 Oct 2001, SDSC