Economic development and biodiversity gain with local community cooperation
Web Service for Cooperation in Biodiversity Modeling
description
Transcript of Web Service for Cooperation in Biodiversity Modeling
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Web Service for Cooperation in Biodiversity Modeling
Karla Donato FookAntônio Miguel V. Monteiro
Gilberto Câmara
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INPA – Instituto Nacional de Pesquisas da Amazônia
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Threatened Threatened
Threatened
MPEG – Museu Paraense Emílio GoeldiINPA – Instituto Nacional de Pesquisas da Amazônia
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Why biodiversity is important?
Biological resources support essential services and sectors Food and Agriculture Pharmaceuticals Medicine Waste treatment
Biodiversity information is fundamental for Preservation of the world’s
fauna and flora Decision-making processes
during the urban and regional planning
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Why model biodiversity? Environmental recovery
Species conservation
Species distribution mapping
Impact of climatic changes
Expansion of invader species
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How scientists work? Scientists working with biodiversity
information employ a variety of Data sources Statistical analysis Modeling tools Presentation or visualization software
These resources use different local and remote platforms
Key resource: acquired knowledgewww.biodiversitas.org.br/f_ameaca/index_lista.htm
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How scientists collaborate? Collaboration among researchers involves
Interaction between scientific models and their implementations
Programs aggregation and experiments results Exchange of data
Web Services helps sharing scientists’ knowledge Improve their studies Apply consolidated knowledge to solve new problems Obtain new knowledge
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Outline Introduction and Motivation
Biodiversity Informatics and GI Web Services
WBCMS – Web Biodiversity Collaborative Modeling Service
Prototype
Conclusions
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Biodiversity Informatics and GI Web Services
Biodiversity data access brings opportunities for new approaches in Ecological analysis Predictive modeling Synthesis and visualization of biodiversity information
GIS technology is moving from isolated, standalone, monolithic, proprietary systems working in a client-server architecture to smaller web-based applications
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Biodiversity Informatics and GI Web Services
Challenges Architectures for workflow creation and managing
Software and middleware development
User interfaces
Protocols for data queries
Analytical and modeling tools
Grid Networking applications
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Approaches to GI Web Services
Spatial Data Integration in Web(Anderson and Moreno-Sanchez, 2003; Pinto et al., 2003; Gibotti et al.,
2005)
Chaining Static and Dynamic Web Services(Tsou and Buttenfield, 2002; Aditya and Lemmens, 2003; Alameh, 2003;
Bernard et al., 2003)
Collaboration and Grid Networking applications in GI Web Services(Foster and Kesselman, 1999; Panatkool and Laoveeraku, 2002; Di et al.,
2003; Foster et al., 2003; Osthoff et al., 2004; Zhao et al., 2004)
These works do not make processing results available to the end-user community
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Outline Introduction and Motivation
Biodiversity Informatics and GI Web Services
WBCMS – Web Biodiversity Collaborative Modeling Service
Prototype
Conclusions
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WBCMS – Web Biodiversity Collaborative Modeling Service
Enable sharing Data Services Knowledge
Knowledge obtained by modeling can be shared through results Model Instance
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Holds Conceptual Information and Metadata
Model
Model generation
Model results
Key concept: Model Instance
• input data – spatial and non spatial• modeling algorithms and its parameters
• maps• reports • ...
• Author• Description • …
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WBCMS provides answers “Which are the modeled species?”
“Where did the data come from?”
“What are the used environmental variables?”
“What is the used algorithm?”
“How to visualize the model?”
“If I have a problem, how can I look for similar results?”
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WBCMS ArchitectureUser withlocal data
User withlocal data
User withlocal data
User withlocal data
Clients
WBCMSCatalogue
Data Handling
Model Instance Catalog Biodiversity Collections(Herbariums, Museums, ...)
Web Services
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Catalogue
InsertModService
CompositModService
ExecuteModService
AggregatorModService
sample data,environmental variables
Services
CatalogModService
Model InstanceCatalog
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Catalogue
InsertModService
CompositModService
ExecuteModService
AggregatorModService
sample data,environmental variables
Services
CatalogModService
Model InstanceCatalog
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Catalogue
InsertModService
CompositModService
ExecuteModService
AggregatorModService
sample data,environmental variables
Services
CatalogModService
Model InstanceCatalog
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Catalogue
InsertModService
CompositModService
ExecuteModService
AggregatorModService
sample data,environmental variables
Services
CatalogModService
Model InstanceCatalog
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Catalogue
InsertModService
CompositModService
ExecuteModService
AggregatorModService
sample data,environmental variables
Services
CatalogModService
Model InstanceCatalog
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Data handling
QueryModService
Model Instance
Model Instance
AccessModService
Model InstanceCatalog
...Client Client
RetrieveModService
Query
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Data handling
QueryModService
Model Instance
Model Instance
AccessModService
Model InstanceCatalog
...Client Client
RetrieveModService
Query
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Data handling
QueryModService
Model Instance
Model Instance
AccessModService
Model InstanceCatalog
...Client Client
RetrieveModService
Query
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Outline Introduction and Motivation
Biodiversity Informatics and GI Web Services
WBCMS – Web Biodiversity Collaborative Modeling Service
Prototype
Conclusions
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Prototype Apache server, PHP and MySQL
OpenModeller Project
OpenModeller Input data
• occurrence points (latitude/longitude)• environmental layers
Result• Species distribution map
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WBCMS and Open Modeller
Modeling Result
Client
OpenModeller Desktop
Client
Modeling Result
Server with WBCMS prototype
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Results
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Visualized files
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Visualized files
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Outline Introduction and Motivation
Biodiversity Informatics and GI Web Services
WBCMS – Web Biodiversity Collaborative Modeling Service
Prototype
Conclusions
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Conclusions Users from species distribution modeling
network can cooperate through the cataloguing of their modeling results
The WBCMS allows the knowledge obtained by one modeler or group of modelers to be shared with other researchers
WBCMS is in its initial phase of development
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Future Work Define the computational environment,
implementing the whole architecture of WBCMS
Perform new experiments with real data and real models and modelers involved
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Thanks
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ReferencesAditya, T. and R. Lemmens (2003). Chaining Distributed GIS Services,
International Institute for Geo-Information Science and Earth Observation.Alameh, N. (2003). "Chaining geographic information web services." IEEE
Internet Computing.Anderson, G. and R. Moreno-Sanchez (2003). "Building Web-Based Spatial
Information Solutions around Open Specifications and Open Source Software." Transactions in GIS 7(4): 447-466.
Bernard, L., U. Einspanier, M. Lutz, et al. (2003). Interoperability in GI Service Chains-The Way Forward. 6th AGILE Conference on Geographic Information Science, Muenster.
CRIA and FAPESP. (2005). "openModeller: Static Spatial Distribution Modelling Tool." Retrieved agosto/2005, from http://openmodeller.cria.org.br/.
Curbera, F., M. Duftler, R. Khalaf, et al. (2002). "Unraveling the Web services web: an introduction to SOAP, WSDL, and UDDI." IEEE Internet Computing.
Di, L., A. Chen, W. Yang, et al. (2003). The Integration of Grid Technology with OGC Web Services (OWS) in NWGISS for NASA EOS Data. HPDC12 (Twelfth IEEE International Symposium on High-Performance Distributed Computing) & GGF8 (The Eighth Global Grid Forum), Seattle, Washington, USA.
Foster, I. and C. Kesselman (1999). Computational Grids. The Grid: Blueprint for a New Computing Infrastructure, Morgan-Kaufman.
Foster, I., J. Vöckler, M. Wilde, et al. (2003). The Virtual Data Grid: A New Model and Architecture for Data-Intensive Collaboration. First Biennial Conference on Innovative Data Systems Research, Asilomar, California.
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ReferencesGibotti, F. R., G. Câmara and R. A. Nogueira (2005). GeoDiscover – a
specialized search engine to discover geospatial data in the Web. GeoInfo 2005 – VII Brazilian Symposium on GeoInformatics, Campos do Jordão, SP, Brazil.
Hall, P. (2004). Biodiversity E-tools to Protect our Natural World. Converging Sciences Conference. Trento, Italy.
Osthoff, C., R. A. d. Almeida, A. C.V.Monteiro, et al. (2004). MODGRID – Um ambiente na WEB para desenvolvimento e execução de modelos espaciais em um ambiente de Grades Computacionais. Petrópolis, LNCC - Laboratório Nacional de Computação Científica.
Panatkool, A. and S. Laoveeraku (2002). Decentralized GIS Web Services on Grid. Open source GIS - GRASS users conference, Trento, Italy.
Pinto, G. d. R. B., S. P. J. Medeiros, J. M. d. Souza, et al. (2003). "Spatial data integration in a collaborative design framework." Communications of the ACM 46(3): 86-90.
Tsou, M. H. and B. P. Buttenfield (2002). "A Dynamic Architecture for Distributing Geographic Information Services." Transactions in GIS 6(4): 355-381.
White, R. (2004). Helping biodiversity researchers to do their work: collaborative e-Science and virtual organisations. Converging Sciences Conference. Trento, Italy.
Zhao, Y., M. Wilde, I. Foster, et al. (2004). Grid middleware services for virtual data discovery, composition, and integration 2nd workshop on Middleware for Grid Computing Toronto, Ontario. Canada, ACM Press.
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Backup Slides
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Approaches Biodiversity Informatics and GI Web Services
Spatial Data Integration in Web Pinto et al. extended the architecture of data integration, which
provides services to find, share and publish sources of data through the Web
Chaining Static and Dynamic Web Services Alameh proposes an architecture for the building of infrastructure
that supports the dynamic linkage of distributed services. • This infrastructure facilitates the integration of GIS data providers with
other information systems Bernard et al. propose the static linkage of GI Web Services to build
up a more a complex task. • The work was applied in estimating road blockage after storms
Collaboration and Grid Networking applications in GI Web Services
Tsou et al. presented a dynamic architecture for distribution of Geographical Information Services with Grid Networking Peer-To-Peer technology.
• A framework based on existent languages, computational architectures and web services was implemented
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Use Case
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Service catalogues Model Instance
Primary Actor: ResearcherScope: Species Distribution Modeling NetworkStakeholders and Interests:
• Researcher - wants to catalog the result of his/her modeling;Success Warranty: the model instance was generated and saved intocatalogTrigger: Researcher calls the web serviceMain Success Scenario:
1. The Researcher selects the web service to catalog the model instance2. The Service prepares the environment to perform the modeling algorithm3. The Service creates the structure with model’s data and metadata tocompose the model instance4. The Service inserts the model instance generated in the catalog
Extensions:2a. Specimens data (local and/or remote) or environmental variables are notavailable2a1. The Service shows message and cancels the Service’s request
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Service accesses Model InstancePrimary Actor: ResearcherScope: Species Distribution Modeling NetworkStakeholders and Interests:
• Researcher – wants to access the model instance;Success Warranty: the model instance was retrieved and
visualizedTrigger: Researcher calls the web serviceMain Success Scenario:
1. The Researcher selects the web service to recover the model
instance2. The Service recovers the model instance3. The Researcher visualizes the model instance
Extensions:2a. Model instance isn’t cataloged2a1. Service shows message and it restarts search process
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Prototype OpenModeller generated files
Different formats: .cfg, .html, .xml, .tif and .png, among others
Visualized Files .html file
• Report generated by the openModeller .xml file
• Input data and metadata of the modeling algorithm, for instance the data related to species occurrence
.png file• Species distribution map obtained by the modeling
process from OpenModeller
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Initial experiment Stored Data
1n