1. Global Lake Ecological Observatory Network - GLEON: Catalyzing Global Team Science based on PRAGMA Peter Arzberger Tim Kratz, Fang-Pang Lin Philip Papadopoulos, Mason Katz Gabriele Wienhausen, Linda Feldman And many more 15 July 2006

3. Yuan-Yang Lake Ecosite Dong Hwa Tower ~900MHz RF Source Fang-Pang Lin

4. Lake Metabolism Website http://lakemetabolism.org

5. Wind Speed Precipitation (mm/5 minutes) Typhoon causes water column mixing Mixing event Source: Tim Kratz

6. Typhoon Typhoons reset algal community composition in Yuan Yang Lake Data courtesy of Dr. J.T. Wu, Academia Sinica Date (2004) Relative Abundance of major algal groups

7. Typhoons: Other Outcomes Access can be difficult during the most interesting times Photo by Peter Arzberger, October 2004

8. PRAGMA’s Founding Motivations The grid is transforming e-science: computing, data, and collaboration The problem remains that the grid is too hard to use on a routine basis Middleware software and people need to interoperate Science is an intrinsically global activity

9. http://www. pragma -grid.net Establish sustained collaborations and Advance the use of the grid technologies for applications among a community of investigators working with leading institutions around the Pacific Rim Overarching Goals PRAGMA Working closely with established activities that promote grid activities or the underlying infrastructure, both in the Pacific Rim and globally.

10. Cindy Zheng, Geon Workshop, 7/20/2006 PRAGMA Grid Testbed AIST OSAKAU TITECH Japan CNIC China KISTI Korea ASCC NCHC Taiwan UoHyd India MU Australia BII IHPC NGO Singapore KU NECTEC Thailand NCSA USA SDSC USA CICESE Mexico UNAM Mexico UChile Chile QUT Australia UZurich Switzerland JLU China MIMOS USM Malaysia IOIT-HCM Vietnam BU USA

11. CCGrid - Singapore 16 – 19 May 2006 Abramson D, Lynch A, Takemiya H, Tanimura Y, Date S, Nakamura H, Jeong K, Hwang S, Zhu J, Lu ZH, Amoreira C, Baldridge K, Lee H, Wang C, Shih HL, Molina T, Li, W, Arzberger P. Deploying Scientific Application on the PRAGMA Grid Testbed: Ways, Means and Lessons. CCgrid 2006 Lee B-S, Tang M, Zhang J, Soon OY, Zheng C, Arzberger P. Analysis of Jobs on a Multi-Organizational Grid Test-bed. CCGrid 2006. Huang W, Huang C-L, Wu, C-H., The Development of a Computational Grid Portal. Accepted CCGrid 2006. Zheng C, Abramson D, Arzberger P, Ayuub S, Enticott C, Garic S, Katz M, Kwak J, Papadopoulos P, Phatanapherom S, Sriprayoonsakul S, Tanaka Y, Tanimura Y, Tatebe O, Uthayopas P. The PRAGMA Testbed: Building a Multi-Application International Grid CCGrid 2006. More information at www.pragma-grid.net

12. PRIME: Providing Students International Interdisciplinary Research Internships and Cultural Experiences preparing the global workplace of the 21 st century Computer Network Information Center (CNIC), Chinese Academy of Sciences Cybermedia Center (CMC), Osaka University, Japan Monash University, Australia National Center for High-performance Computing (NCHC), Taiwan

13. PRIUS: Pacific Rim International UniverSities Osaka University Exchange among PRAGMA Sites Lectures from PRAMGA members PRAGMA 11 Oct 2006 – to expand PRIUS http://prius.ics.es.osaka-u.ac.jp/en/index.html

14. PRAGMA Future Meetings PRAGMA 11 –Osaka University, Japan, approx. 15 – 17 October 2006 –Preparing Future Generations; in conjunction with PRIUS program PRAGMA 12 –NECTEC, Kasetsart University, Thailand, Spring 2007 –Advancing Collaborations with ThaiGrid PRAGMA 13 –NCSA, Illinois, USA, Fall 2007 –PRAGMA Engagements in Cyberenvironments PRAGMA 14 –NCHC, Taiwan, Spring 2008 –Living Grids; Held in conjunction with Taiwan Grid Activities

15. Towards a Global Lake Ecological Observatory Network Tim Kratz Director, Trout Lake Station Center for Limnology University of Wisconsin-Madison Yuan Yang Lake, Taiwan ; photo by Matt Van de Bogert

16. From Cole, J. J., N. F. Caraco, G. W. Kling, and T. K. Kratz. 1994. Carbon dioxide supersaturation in the surface waters of lakes. Science 265:1568-1570 Mirror Lake, New Hampshire Lake Air Many lakes are supersaturated in CO 2 Source: Tim Kratz

17. From Cole, J. J., N. F. Caraco, G. W. Kling, and T. K. Kratz. 1994. Carbon dioxide supersaturation in the surface waters of lakes. Science 265:1568-1570 Of 4665 samples from 1835 lakes worldwide, 87% were supersaturated Why? Source: Tim Kratz

18. What is the “Global Lake Ecological Observatory Network?” A grassroots network of –People: lake scientists, engineers, information technology experts –Institutions: universities, national laboratories, agencies –Programs: PRAGMA, AS-Forest Biogeochemistry,US-LTER, TERN, KING, EcoGrid, etc. –Instruments –Data Linked by a common purpose and cyberinfrastructure With a goal of understanding lake dynamics at local, regional, continental, and global scales Source: T. Kratz March 2005

19. Vision and Driving Rationale for GLEON A global network of hundreds of instrumented lakes, data, researchers, students, Predict lake ecosystems response to natural and anthropogenic mediated events –Through improved data inputs to simulation models –To better plan and preserve freshwater resources on the planet

20. Programs -Australia -Canada -China -Finland -Florida -New Zealand -Israel -South Korea -Taiwan -United Kingdom -Wisconsin 1 st : San Diego Mar. 7-9, 2005 Source: T. Kratz Steering Committee -Peter Arzberger, UCSD, USA -David Hamiltion, University of Waikato, New Zealand -Tim Kratz, University of Wisconsin, USA -Fang-Pang Lin, NCHC, Taiwan 2 nd :Townsville Mar. 28-29, 2006

21. Second GLEON and CREON Workshop: Townsville AU 28 – 29 March 2006 Agreement on specific lake analysis Agreement on data collection from coral reef Demonstrations of technologies Agreement of future meetings Third Meeting in Taiwan 3 – 4 October 2006

22. Scalable instrumentation and cyberfrastructure is critical We can do this scale now http://lakemetabolism.org Source: Tim Kratz

23. Problematic, but possible with today’s cyberinfrastructure Scalable instrumentation and cyberfrastructure is critical Source: Tim Kratz lakemetabolism.org

24. Scale needed to answer regional/continental questions Not currently possible

25. Addressing the Scaling Challenge NSF NEON Award Collaborative Research: Automating Scaling and Data Processing in a Network of Sensors: Towards a Global Network for Lake Metabolism Research and Education –UCSD, UWI, IU, SUNY-Binghamton Automate –Instrument management –QA/QC and Event Detection Service Oriented Architecture Broaden Involvement of Students

26. Building Community Based, Grass-Roots Research Networks: The Cases of Global Lake Ecological Observatory Network (GLEON) and of Coral Reef Ecological Observatory Network (CREON) Develop a robust, persistent infrastructure and interface for data sharing and analysis Assist specific sites in establishing monitoring systems to produce data Hold a series of working meetings and engage other network projects A proposal to

27. Network-Level Applications Data Ingestion System Data Integration System Command and Control Buoy 1Buoy N ……….……. S 1 …. S 1 S L S k S 1 S M ………. Raw data QA/QC Transform Event Detection Mining Data Stream Workflows Site Services Interface QA/QC Transform QA/QC Transform Analysis and Modeling System Real-time Active Data Warehouse … Sensors Site Cyberdashboard/Portal Network-Level Applications Generalize Site-level architecture Source: Tony Fountain

28. Network Level Conceptual Architecture Site Services Interface Analysis and Modeling System Real-time Active Data Warehouse Site Services Interface Analysis and Modeling System Real-time Active Data Warehouse Site Services Interface Analysis and Modeling System Real-time Active Data Warehouse Network-Level Applications Network-Level Cyberdashboard/Portal Source: Tony Fountain

29. Second GLEON and CREON Workshop: Townsville AU 28 – 29 March 2006 Agreement on specific lake analysis Agreement on data collection from coral reef Demonstrations of technologies Agreement of future meetings GLEON and CREON Third Workshop, Taiwan, 3 – 4 October 2006

30. References Kratz, Timothy K., Peter Arzberger, Barbara J. Benson, Chih-Yu Chiu, Kenneth Chiu, Longjiang Ding, Tony Fountain, David Hamilton, Paul C. Hanson, Yu Hen Hu, Fang-Pang Lin, Donald F. McMullen, Sameer Tilak, Chin Wu. (in press). Toward a Global Lake Ecological Observatory Network. Proceedings of the Karelian Institute. Porter, J., P. Arzberger, H. Braun, P. Bryant, S. Gage, T. Hansen, P. Hanson, F. Lin, C. Lin, T. K. Kratz, W. Michener, S. Shapiro, and T. Williams. 2005. Wireless sensor networks for ecology. Bioscience 55:561-572. Sensors for Environmental Observations, National Science Foundation Workshop Report (Seattle WA, Dec 2004) 2005 http://www.wtec.org/seo http://www.wtec.org/seo

31. Future Activities Link together a collection of networks –Work with partners in PRAGMA: NCHC, NECTEC, NARC, and others U Waikato, NIGLAS, … Create test bed for sensors and sensor network

32. New Paradigm: Global Team Science U.Waikato D.Hamilton Models NCHC F.P.Lin Maintain YYL Parallelize Codes U.Wisconsin T.Kratz Maintain Trout Bog Lake Metabolism UCSD F.Vernon, S.Peltier, T.Fountain P.Arzberger ROADNet, Telescience Moore Fnd, PRAGMA NIGLAS B.Q Qin Maintain Taihu Physical Limnology Kangwon U B.Kim Maintain Soyang Public Policy

33. Acknowledgements PRAGMA –Philip Papadopoulos (UCSD) –Mason Katz, Wilfred Li, Kim Baldridge, Tomas Molina, Cindy Zheng –Fang-Pang Lin (NCHC) –And many others at all 28 institutions, in particular the Steering Committee GLEON –Tim Kratz (U WI) –David Hamilton (U Waikato) –Fang-Pang Lin (NCHC) –And others at 10 other sites CREON –Sally Holbrook (UCSB) –Stuart Kininmonth (AIMS) PRIME –Gabriele Wienhausen –Linda Feldman –All Host sites and students PRIUS –Shinji Shimojo (Osaka) –Susumu Date (Osaka) CAMERA –Larry Smarr –Paul Gilna NSF –Bill Chang –Many others Gordon and Betty Moore Foundation National Institutes of Health

35. e-science’s New Frontier: Merging of Science and Information Technology – GLEON and PRAGMA’s Activities Previously Unobtainable Observations and Understanding Enabling Technology Advance science Science Drivers Focus development Persistent Infrastructure Broaden impact Education & Capacity Building Develop human resources Sustained Collaboration Build teams and trust

36. 2020 Vision for the National Science Foundation Strategic Priority 1: Ensure the Nation maintains a position of eminence at the global frontier of fundamental and transformative research, emphasizing areas of greatest scientific opportunity and potential benefit. Strategic Priority 2: Sustain a world- class S&E workforce and foster the scientific literacy of all our citizens. Strategic Priority 3: Build the Nation’s basic research capacity through critical investments in infrastructure, including advanced instrumentation, facilities, cyberinfrastructure, and cutting-edge experimental capabilities. http://www.nsf.gov/pubs/2006/nsb05142/nsb05142.pdf

37. NSF Environmental Observing Systems New collaborative environments (simulation, computation, visualization, and knowledge systems) are needed to facilitate the integration of research, education, and dialog across a wide range of biological, geophysical, and social sciences. Data repositories and facilities for synthesis and prediction Characteristics Source: Liz Blood Transformative in understanding complexity of natural and human environments Geographically distributed infrastructure connected via cyberinfrastructure into national observatory network Apply emerging technologies (sensor, analytical, communication, information) to investigate the structure, dynamics, and evolution of systems in the United States and forecast change.

38. Frequency of measurement Spatial extent Annual 100 km MonthlyWeeklyDailyHourlyMin. Sec. 10 km 1 km 100 m 10 m 1 m 10 cm Existing Sensor Networks random selection from Ecology 2003 Source: John Porter et al., Bioscience, 2005 Sensor networks allow high frequency observations over broad spatial extents