Data-Model Assimilation: Collaboration, Integration, & Transformation

1. Data-Model Assimilation: Collaboration, Integration, & Transformation GLOBAL CARBON CYCLE ATMOSPHERIC COMPOSITION Ecological Forecasting: a Grand Challenge LAND-USE & LAND-COVER CHANGE ECOSYSTEMS GLOBAL WATER CYCLE HUMAN CONTRIBUTIONS & RESPONSES/DECISION SUPPORT CLIMATE VARIABILITY & CHANGE

2. Challenge: Integration and Need for Modeling Framework From Climate Change 2001: The Scientific Basis

3. Forecasting: The Challenge of Scale 1000 km2 10 km2 ha m2 µm2 Down-scaling for Verification Up-scaling for Prediction

4. 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

5. 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

6. Advancing Theory in Biology • Develop new conceptualizations and theoretical approaches to identify fundamental principles that traverse all levels of biological complexity • NSF 07-556

7. National Ecological Observatory Network (NEON) “Opening new horizons in the science of large-scale ecology”

8. Transformative 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 EOS

9. 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 NSF Earth Observing Systems National Ecological Observatory Network (NEON) WATERS

10. Dynamics of Coupled Natural and Human Systems(CNH) NSF 07-598 • 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: • 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.

11. Enabling Cyberinfrastructure Static Sensor Node Cable NIMS Node NIMS Node Cable Sensor Sensor Sensor Sensor Microserver Sensor Node Package Microserver Sensor Node Package National Ecological Observatory Network (NEON) Embedded CI Web Portals System CI Collaboration Virtual Org. Visualization

12. 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 ThemesCDI 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.

13. CDI Examples • 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.

14. 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.

15. Sustainable Digital Data Preservation and Access Network Partners (DataNet)NSF 07-601 • 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.

16. 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

17. NEON International Observatory Prototyping Testbed

18. NEON R&D Cyberinfrastructure: Bringing Resources to Researchers M.Brown • Web Services • metabolism models • intelligent agents • data retrieval Global Connectivity • Web Services • Quality control • Event detection

19. NSF Centers • NCEAS • National Center for Ecological Analysis and Synthesis • http://www.nceas.ucsb.edu/ • NESCent: • National Evolutionary Synthesis Center • http://www.nescent.org/

20. 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.

21. 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