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Ecogrid: from Field Observation to Spatial Knowledge

Ecogrid: from Field Observation to Spatial Knowledge. 5 April 2005 Floris Sluiter Computational Bio- and Physical Geography, UvA. Sub Program 1.4 of the VL-e program. Two projects on biodiversity: Bambas Parameter Optimization and Data Assimilation in Bird Avoidance Models

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Ecogrid: from Field Observation to Spatial Knowledge

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  1. Ecogrid: from Field Observation to Spatial Knowledge 5 April 2005 Floris Sluiter Computational Bio- and Physical Geography, UvA

  2. Sub Program 1.4 of the VL-e program Two projects on biodiversity: • Bambas • Parameter Optimization and Data Assimilation in Bird Avoidance Models • Ecogrid • The topic of today

  3. Co-workers: • Willem Bouten, chair CBPG • Guido van Reenen, CBPG (Analysis Data Model) • Floris Sluiter, CBPG (Design & Implementation) VOFF (10 nature organizations) • Victor Mensing, Vlinderstichting • Dirk Zoetebier, Sovon Special Thanks to: • Aart Jan van der Linden, Talmon Communications (portal prototype implementation)

  4. Overview • Ecogrid Aims • Example: Red-backed Shrikes • Data Acquisition • Spatial databases • Ecogrid System Overview • Working Prototype: • Data Acquisition Portal • Science/Analysis Portal • Remarks & Questions

  5. Ecogrid: the Aims SP1.4 • Construct a virtualdatabase that is connected to geographically distributed databases which contain information on the distributions of species, on landscapecharacteristics and on weather. • Develop generic methodologies and toolsfor scale conversions, to be able to integrate and interpret data that are observed at different spatial scales. • Use this infrastructure across the boundaries of organizations to identify: • Spatial food web structures • Biodiversity hotspots • Effects of changed land use.

  6. Example: Insect diversity and Red-backed Shrikes

  7. } Nitrogen dep.

  8. The Netherlands has one of the worlds most extensive and densest networks for collecting data on the spatial and temporal distributions of flora and fauna Data Acquisition Spreadsheets/’databases’ Notebook Biologist

  9. Data Acquisition (continued) • Combine biological data with data on • Weather & Climate data • Landscape characteristics • Land use • Soil • Vector maps of roads/cities and other infrastucture • Vegetation • … Some of these datasets we will host ourselves, others we will connect to through web services

  10. Spatial databases:Geographic Information Systems (GIS) • Spatial functions to query (SQL) within and across layers: • Equals() • Disjoint() • Intersects() • Touches() • Crosses() • Within() • Contains() • Overlaps() • Special indexing techniques (GisT) ‘Layers’ build with these data types, stored as tables inPostgreSQL/PostGIS.

  11. Ecogrid system: overview Data Acquisition Portal SciencePortal Landscape Weather EcogridVirtual Meta Database . . . . . . . . Spotfire Data mining modules Model Experiments Scale conversion Modules Geostatistics Processed data BAMBAS Database Sovon Vlinder-stichting VL-eScience Research Environment

  12. Ecogrid system: Prototype TaxonomyFenology Codes Data Acquisition Portal SciencePortal Landscape Weather EcogridVirtual Meta Database . . . . . . . . Spotfire Data mining modules Model Experiments Scale conversion Modules Geostatistics Processed data BAMBAS Database Sovon Vlinder-stichting VL-eScience Research Environment

  13. Ecogrid: Portal Prototype

  14. Ecogrid: Portal Prototype

  15. Ecogrid: Portal Prototype

  16. Ecogrid: Portal Prototype

  17. Ecogrid: Portal Prototype

  18. Concluding Remarks • PostgreSQL (and Postgis) are especially suited for large scientific databases • 12 April we will present the prototype to all the partners in this project • By the end of the year all the databases will be filled and we will have online data aqcuisition. • Then we will shift our focus on using the data and concentrate on Analysis and Datamining

  19. Questions? http://www.vl-e.nl/

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