Species Distribution Modeling

Alexandre Copertino JardimAntonio Miguel Vieira

MonteiroKarla Donato Fook

Lúbia VinhasSilvana Amaral

Scientific Workshop In Geoinformatics, INPE, 18 February 2009

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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

...

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The SD modeling process

Geographic position

Occurrence data

Precipitation

Topography

Temperature

Environmental data

Predictive distribution

Alg

ori

thm

NDVI

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GIS integration

FilesFile

GIS

Initially

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GIS integration

Files

GISData Source

W*SDB

Reviewed architecture

Algorithms

Other libraries can be integrated

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GIS integration – loose coupling

TerraView: TerraLib–OM Plugin:

Allowing the user to work with the concept

of data source

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Environmental Data

http://www.gbif.org

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 Researcher Researcher

WBCMSWeb 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

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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

Researcher Researcher

Researcher

Model Instances CataloguesBiodiversity Collections

WS_2 WS_N

Map Servers

WS_1

RepositoriesCatalogue

ModelProcessorAccessProcessorCatalogueProcessor

WFS(TeOGC)

WBCMS Architecture

WBCMS

ModelProcessorAccessProcessorCatalogueProcessor

Web

Client applications

Researcher

Researcher Researcher

Researcher

Model Instances CataloguesBiodiversity Collections

WS_2 WS_N

Map Servers

WS_1

RepositoriesCatalogue

ModelProcessorAccessProcessorCatalogueProcessor

WFS(TeOGC)

Client Applications

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Catalogue Client Application

OpenModellermodelling result

statusmsg

Model Instances

WBCMS

Model Instance

Web Services

Biodiversity Data

Researcher

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Access Client Application

Model Instance

Model Instance

Query

Researcher

WBCMS

Model Instances

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Species Distribution Maps

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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