Transcript Slide 1

Data-Model Assimilation:
Collaboration, Integration, & Transformation
GLOBAL CARBON CYCLE
ATMOSPHERIC
COMPOSITION
Ecological Forecasting: a Grand Challenge
ECOSYSTEMS
LAND-USE &
LAND-COVER
CHANGE
GLOBAL
WATER
CYCLE
CLIMATE VARIABILITY
& CHANGE
HUMAN CONTRIBUTIONS
& RESPONSES/DECISION
SUPPORT
Challenge: Integration and Need for Modeling Framework
From Climate Change 2001: The Scientific Basis
Forecasting: The Challenge of Scale
1000 km2
10 km2
ha
m2
µm2
Up-scaling for
Prediction
Down-scaling for
Verification
Reliable Ecological Forecasts
• Project potential consequences of global change
• Provide options for sustaining ecosystems and their goods and
services
• Basic and applied research advances in knowledge, tools,
people
• Incorporate observations, experimental results, process studies
at all scales
• Require interdisciplinary effort (physical – biological-social
sciences)
• Necessitate estimates of uncertainty
• Cyberinfrastructure reliant
NSF Opportunities
• Basic Research
– Fundamental Theory
– Coupled systems
– Scale, Integration
• Technology
– Sensors & Sentinel, QA/QC, wireless
• Cyberinfrastructure
– Data
– Software, interoperability
– Visualization
• Organization – Governance
– Virtual, Centers, Observatories, Networks
Advancing Theory in Biology
- Develop new conceptualizations and
theoretical approaches to identify
fundamental principles that traverse
all levels of biological complexity
- NSF 07-556
National Ecological Observatory Network (NEON)
“Opening new horizons in the science of large-scale ecology”
Transformative
NSF EOS
Grand Challenges
Scale and scope of science addressing
Capacity to conduct research
Application of emerging technologies
Access to data, knowledge, and tools
Cultural change in the conduct of science
NSF Earth Observing Systems
National Ecological Observatory Network (NEON)
NSF Observing Networks
Partnering Opportunities
• Sensors & Sensor Networks
• Communication (cross-platform)
• Collaboratories & Telepresence
• System Integration
• Data Repositories & Informatics
• Computation/ Visualization
• Modeling/Forecasting
• Decision Support Systems
• Education & Training
• Science in the human dimension
• Social Sciences
WATERS
Dynamics of Coupled Natural and Human
Systems (CNH) NSF 07-598
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The Dynamics of Coupled Natural and Human Systems competition promotes
quantitative, interdisciplinary analyses of relevant human and natural system processes
and complex interactions among human and natural systems at diverse scales.
•
CNH projects include three integrative elements:
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An integrated, quantitative, systems-level method of inquiry is essential. Because of
the complex nature of systems under investigation, treatment of non-linearities,
feedback processes, and integration across temporal or spatial scales is necessary.
Quantitative methods may include conceptual, mathematical, or computational
models; numerical simulation; artificial intelligence techniques; statistics;
visualization; or database development. Mathematical models should include
appropriate estimates of uncertainty, and experiments should assess power and
precision.
•
Education must be addressed and integrated effectively.
•
A global perspective is encouraged. When appropriate and practical, specific
international collaborations and networks for research and education are encouraged.
Enabling Cyberinfrastructure
National Ecological Observatory Network (NEON)
Embedded CI
Web Portals
Static
Sensor Node
Cable
NIMS
Node
NIMS
Node
Cable
Sensor
Sensor
Sensor Sensor
Microserver
Sensor Node
Package
Microserver
Sensor Node
Package
System CI
Collaboration
Virtual Org.
Visualization
Cyber-enabled Discovery and Innovation (CDI)
NSF 07-603
create revolutionary science and engineering research outcomes made
possible by innovations and advances in computational thinking.
Computational thinking is defined comprehensively to encompass
computational concepts, methods, models, algorithms, and tools.
CDI Themes
CDI seeks ambitious, transformative, multidisciplinary research proposals
within or across the following three thematic areas:
•
•
•
From Data to Knowledge: enhancing human cognition and generating new
knowledge from a wealth of heterogeneous digital data;
Understanding Complexity in Natural, Built, and Social Systems:
deriving fundamental insights on systems comprising multiple interacting
elements; and
Building Virtual Organizations: enhancing discovery and innovation by
bringing people and resources together across institutional, geographical
and cultural boundaries.
CDI Examples
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Complexity issues Interdisciplinary, geographically diverse, virtually connected,
nonlinear dynamic networks that predict and control changes across multiple
infrastructures, length and time scales, with fidelity and the ability to handle
huge volumes of data could involve a large number of disciplines and
organizations.
•
Living systems function through the encoding, exchange, and processing of
information. New research seeking similar understanding of the communication
flowing at other systemic levels such as chemical pathways, cell signaling, mate
selection, or ecosystem services feedback poses a challenge to information
science to develop more advanced cyber tools for digitally representing and
manipulating the increasingly complex data structures found in natural and
social systems.
•
Theoretical foundations offering tools for understanding, modeling, and
analysis of large-scale, complex, heterogeneous networks. Another area is
biological networks, whose understanding remains rudimentary. New,
realistic models involving complex coupled networks include communication
systems, the human brain, and social networks. All of these cases call for better
understanding of network structure, function, and evolution. This example spans
all three CDI themes: massive sets of network data should produce
knowledge of patterns across many temporal and spatial scales; networks,
man-made, social, or natural, embodiments of complex systems of interaction;
finally, VOs themselves consist of networks at different scales of interaction and,
in turn, study networks.
CDI Examples
• Develop techniques to forecast critical events in geophysics and
predict their impact on society. Central is the ability to adaptively
configure the resolution of numerical models and real-time
observing networks; to zoom in and follow important dynamic
features (ocean eddies, earthquakes, volcanic eruptions, landslides,
storms, flash floods, hurricanes, algal blooms, etc.); and to predict
their impact on human society, infrastructure, and ecosystem
services.
• Model, simulate, analyze, and validate complex systems with
large data sets. E.g. predictive understanding of ecological and
evolutionary processes at multiple scales (biological sciences)
• Understanding human/environmental interactions requires the
merging of data across multiple scales, such as remote
sensing data, surveys of households, and ecological data.
Sustainable Digital Data Preservation and
Access Network Partners (DataNet)
NSF 07-601
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major challenges of this scientific generation: how to develop the new
methods, management structures and technologies to manage the
diversity, size, and complexity of current and future data sets and data
streams.
These organizations will integrate library and archival sciences,
cyberinfrastructure, computer and information sciences, and domain
science expertise to:
• provide reliable digital preservation, access, integration, and analysis
capabilities for science and/or engineering data over a decades-long
timeline;
• continuously anticipate and adapt to changes in technologies and in user
needs and expectations;
• engage at the frontiers of computer and information science and
cyberinfrastructure with research and development to drive the leading edge
forward; and
• serve as component elements of an interoperable data preservation and
access network.
Research Coordination Networks
- To encourage and foster new
interactions among scientists,
- Promote new directions in
research directions
- Stimulate advances in a field
- NSF 06-567
NEON
International
Observatory
Prototyping
Testbed
NEON R&D
Cyberinfrastructure: Bringing Resources to Researchers
Web Services
•metabolism models
•intelligent agents
•data retrieval
Global ConnectivityM.Brown
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12
22-Aug
0
23-Aug
24-Aug
25-Aug
Date
26-Aug
27-Aug
28-Aug
Precipitation
Surface
0.5 meters
1 meter
1.5 meters
2 meters
2.5 meters
3 meters
Precipitation
20
(mm per 5 minute interval)
Water Temperature (°C)
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Web Services
•Quality control
•Event detection
NSF Centers
- NCEAS
- National Center for Ecological
Analysis and Synthesis
- http://www.nceas.ucsb.edu/
- NESCent:
- National Evolutionary Synthesis
Center
- http://www.nescent.org/
Center for Research at the Interface of the
Mathematical and Biological Sciences (CIMBS)
NSF 07-597
• This solicitation requests proposals to establish a Center
to stimulate research and education at the interface of
the mathematical and biological sciences. The Center
will serve the biological and mathematical communities
by providing mechanisms to foster synthetic,
collaborative, cross-disciplinary studies. It will play a
pivotal role by improving understanding and modeling
of biological problems that can be gained only by
using approaches of mathematical, statistical and
computational biology. The Center also will play a
critical role in addressing national needs, including the
area of plant and animal infectious disease modeling,
and provide knowledge that will be useful to policy
makers, government agencies, and society.
NSF Opportunities
• Basic Research
– Fundamental Theory
– Coupled systems
– Scale, Integration
• Technology
– Sensors & Sentinel, QA/QC, wireless
• Cyberinfrastructure
– Data
– Software, interoperability
– Visualization
• Organization – Governance
– Virtual, Centers, Observatories, Networks