Informatics at UCSB, MSI, and NCEAS

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http//knb.ecoinformatics.org
http//seek.ecoinformatics.org
SEEK Enabling Ecology and Biodiversity Science
Through Cyberinfrastructure
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Data Entropy
Time of publication
Specific details
General details
Retirement or career change
Information Content
Accident
Death
Time
(Michener et al. 1997)
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What Users Really Want
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SEEK Overview
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Morpho
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SEEK

• Science Environment for Ecological Knowledge
• EcoGrid
• Access to environmental data
• Analysis and Modeling System
• Modeling scientific workflows
• Semantic Mediation System
• Smart data discovery and integration
• Knowledge Representation
• Classification and Nomenclature
• Biodiversity and Ecological Analysis and Modeling

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Lotka-Volterra Predator Prey Model
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SEEK EcoGrid

• Integrate diverse data networks from ecology,
  biodiversity, and environmental sciences
• Grid-standardized interfaces
• Metadata-mediated data access (EML)
• Computational access
• Pre-defined analytical services
• On-the-fly analytical services

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EcoGrid client interactions

• Modes of interaction
• Client-server
• Fully distributed
• Peer-to-peer
• EcoGrid Registry
• Node discovery
• Service discovery
• Aggregation services
• Centralized access
• Reliability
• Data preservation

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Semantic Mediation

• Label data with semantic types
• Label inputs and outputs of analytical components
  with semantic types
• Use reasoning engines to generate transformation
  steps
• Beware analytical constraints
• Use reasoning engine to discover relevant
  components

Data
Ontology
Workflow Components
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Ecological ontologies

• What was measured (e.g., biomass)
• Type of measurement (e.g., energy)
• Context of measurement (e.g., Psychotria
  limonensis)
• How it was measured (e.g., dry weight)

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Growl Ontology Viewer Showing the Measurements
Ontology
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The SEEK Prototype Ecological Niche Modeling
Geographic Space
Ecological Space
Biodiversity information e.g., data from museum
specimens
ecological niche modeling
occurrence points on native distribution
Geospatial and remotely sensed data
Results taken to integration with other data
realms (e.g., human populations, public health,
etc.)
Native range prediction
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Species prediction map
Predicted Distribution Amur snakehead (Channa
argus)
Image from http//www.lifemapper.org
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Future Scenarios
Future scenarios based on general circulation
models (GCMs) present diverse visions of global
climate futures. The implications of these
different futures for biodiversity are only now
being explored
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SEEK/Kepler Mammal-CC Project

• Build pipelines for automated processing of
  CC/biodiversity analyses
• Prototype application to mammals of Western
  Hemisphere

• 2000-3000 species
• 2 algorithms
• 100 models/species/algorithm
• 500,000 1,000,000 models
• Test large-scale implementation of Kepler
• Provide a hemisphere-wide
  view of mammal diversity
• Provide a massive comparison of CC implications
  as function of
• region
• clade
• scenario
• Enable many other parallel apps

2-3 dispersal scenarios
2 major evolutionary-computing algorithms (GA and
NN)
15-20 GCM scenarios, including all IPCC scenarios
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Networking
Biomedical Informatics Research Network
CHESS
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Education
Data Sharing
Cultural Change
IM
Best Practices
Advanced Computation
SEEK New Faculty Postdoc Workshop January 5-9,
2004 70 applicants 16 slots
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Citizen Science