Species Distribution Modeling Alexandre Copertino Jardim Antonio Miguel Vieira Monteiro Karla Donato Fook Lúbia Vinhas Silvana Amaral Scientific Workshop.

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Presentation transcript:

Species Distribution Modeling Alexandre Copertino Jardim Antonio Miguel Vieira Monteiro Karla Donato Fook Lúbia Vinhas Silvana Amaral Scientific Workshop In Geoinformatics, INPE, 18 February 2009

2 Context  The project involves three institutions: CRIA (Reference Center on Environmental Information), Poli (Escola Politécnica/ USP), and INPE.  openModeller’s project goal is to develop a framework to facilitate the work of scientists in predictive modeling of species distribution:  develop a component-based modeling framework with reusable modules compliant with web services technology  enable the existence of multiple interfaces (web, desktop, command line, web service)  facilitate access to distributed biological and environmental data networks ...

3 The SD modeling process Geographic position Occurrence data Precipitation Topography Temperature Environmental data Predictive distribution Algorithm NDVI

4 GIS integration Files File GIS Initially

5 GIS integration Files GIS Data Source W*S DB Reviewed architecture Algorithms Other libraries can be integrated

6 GIS integration – loose coupling TerraView: TerraLib–OM Plugin: Allowing the user to work with the concept of data source

7 Environmental Data Alexandre Jardim in a Master student, working on creating a Web Environmental Catalogue Service: - an ontology for environmental data in the domain of SDM - a WS that identifies data sources exporting data as WCS and that makes a mapping between its metadata and the SDM ontoloy - a client interface to the WECS and openModeller - evaluate the WCS specification for the SDM domain

Web Client applications Researcher WBCMS Web Biodiversity Collaborative Modelling Services Client Applications Model instances Catalogue Karla Fook in her phD work proposes an approach for sharing species distribution modeling on Web Publish modeling experiments and their provenance, to make it available into catalogues, and to enable researchers to perform new models based in catalogued model instances Sharing modeling experience

9 The model instance includes data and metadata about the model, its generation process, and experiment results. Which species are being modelled? Where does the data come from? Which environmental variables and algorithms are being used? If I have a question, how can I look for similar results? Model Instance

WBCMS Architecture WBCMS ModelProcessorAccessProcessorCatalogueProcessor Web Client applications Researcher Model Instances Catalogues Biodiversity Collections WS_2WS_N Map Servers WS_1 Repositories Catalogue ModelProcessorAccessProcessorCatalogueProcessor WFS (TeOGC)

WBCMS Architecture WBCMS ModelProcessorAccessProcessorCatalogueProcessor Web Client applications Researcher Model Instances Catalogues Biodiversity Collections WS_2WS_N Map Servers WS_1 Repositories Catalogue ModelProcessorAccessProcessorCatalogueProcessor WFS (TeOGC) Client Applications

12 Catalogue Client Application OpenModeller modelling result status msg Model Instances WBCMSWBCMS Model Instance Web Services Biodiversity Data Researcher

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14 Access Client Application Model Instance Query Researcher WBCMSWBCMS Model Instances

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23 Species Distribution Maps

24 Final Comments  The conceptual framework of web services supplies a base for development of collaborative environment for species distribution modelling  WBCMS architecture  Allows sharing experiments in a species distribution network  Enables researchers to perform new models based in previous ones  Allows comparing results  Experiments have demonstrated the viability of the proposals and ideas  Future work  More complex queries  Model instances reuse statistics  Make Web Biodiversity Collaborative Modelling Services (WBCMS) available