1. Oceans Observations Environmental Obs Satellites Earth System Modeling Cyberinfrastructure in an Era of Observation and Simulation EarthScopeWater Eva Zanzerkia, NSF GEO/EAR

2. This Talk Context at the National and Agency scale CIF21 Data Management What this means for CUAHSI

3. Framing the Challenge: Science and Society Transformed by Data  Modern science  Data- and compute-intensive  Integrative, multiscale  Multi-disciplinary Collaborations for Complexity  Individuals, groups, teams, communities  Sea of Data  Age of Observation  Distributed, central repositories, sensor- driven, diverse, etc

4. NSF ACCI: Innovation and New Paradigms Multiple communities must engage rapidly, integrate observations, expertise o New multidisciplinary research communities and teams o Teams notified of events by social networks, mobile Simulations by global teams  New types of compute, data, collaboration and software infrastructure Comprehensive Computational and Data- Enabled Science & Engineering (CDS&E)  Fundamental to support 21 st century science and engineering

5. New Budget Thrust for 2012: CIF 21 Broad Principles of CIF21  Comprehensive and integrated cyberinfrastructure to transform research, innovation and education  Focus on computational and data-intensive science to address complex problems Increase of $117 million over FY 2010 enacted level Four major components Caveat: This is only the president’s budget request to congress

6. Discovery Collaboration Education Organizations Universities, schools Government labs, agencies Research and Medical Centers Libraries, Museums Virtual Organizations Communities Expertise Research and Scholarship Education Learning and Workforce Development Interoperability and operations Cyberscience Networking Campus, national, international networks Research and experimental networks End-to-end throughput Cybersecurity Computational Resources Supercomputers Clouds, Grids, Clusters Visualization Compute services Data Centers Data Databases, Data repositories Collections and Libraries Data Access; storage, navigation management, mining tools, curation, privacy Scientific Instruments Large Facilities, MREFCs,telescopes, Colliders, shake Tables, laboratory, field deployment, Sensor Arrays Software Applications, middleware Software development and support Cybersecurity: access, authorization, authentication New Computational Resources Community Research Networks Access and Connections to Resources CIF21: Four Thrust Areas Data-Enabled Science

7. Data-Enabled Science Data Services Program (data)  Provide reliable digital preservation, access, integration, and analysis capabilities for science and/or engineering data over a decades-long timeline Data Analysis and Tools Program (information)  Data mining, manipulation, modeling, visualization, decision- making systems Data-intensive Science Program (knowledge)  Intensive disciplinary efforts, multi-disciplinary discovery and innovation Observations Models Climate GIS Remote Sensing

8. New Computational Infrastructure Computational and data-enabled resources  HPC, Clouds, Clusters, Data Centers Long-term software for science and engineering  Sustained software development and support Discipline-specific activities  Services, tools, compute environments that serve specific research efforts and communities Wyoming SCS

9. Access and Connectivity Network connections and engineering program  Real-time access to facilities and instruments; Begins to tie in MREFC activities  Integration and end-to-end performance to provide seamless access from researcher to resource Cybersecurity – from innovation to practice  Deployment of identity management systems  Development of cybersecurity prototypes

10. Community Research Networks New multi-disciplinary research communities  Address challenges beyond individuals and disciplinary research communities  Support and optimize collaboration across small, mid-level and large community networks Advanced research on community and social networks  Structures, leadership, fostering and sustainability  “virtuous cycle” providing feedback through formal evaluation and program iteration

11. CIF21 – Geosciences Foci GEO plans to leverage substantial CI investments  Connect Well-established facilities: ES, OOI, IRIS, UNAVCO, IEDA, NCAR, CIG, CUAHSI,etc....  EAR Geoinformatics program  Participation in NSF-wide activities: PetaApps, SI2  Partnerships with other agencies and industry Long-term plan: connect resources, science, users through National cyberinfrastructure  New and enhanced computational platforms, tools, data centers to analyze, manipulate, visualize and share large and complex data sets  a framework for open and easy access of all geoscience data and integrationg with other domains  Infrastructure and technology for retrieving and sharing observational data  Sustained training programs to create a workforce capable of multi-disciplinary science

12. EarthCube GEO and OCI are working in partnership to support the development of a geosciences wide cyberinfrastructure DCL: nsf11065 http://www.nsf.gov/pubs/2011/nsf11065/nsf11065.j sp?WT.mc_id=USNSF_179 Webinar July 11, 2011. Early Fall: charrette meeting to bring the geosciences community together and focus a design Prototypes (up to 3) will be supported in early Spring

13. Multiple Modes of Support Are Necessary for EarthCube and CIF21 “Modes of support” that are essential to build CIF21 infrastructure and to engage in CIF21 activities.  Focused grants to individual PIs or small groups  Focused programs that are community driven  Small centers  Large national centers  Cyber-enhanced field programs  Cyber-enhanced observing facilities and MREFC projects  NSF-wide initiatives  Education, outreach, and training activities (EOT)

14. Modes of Support Data-Enabled Science New Computational Infrastructure Access and Connection Networks EarthCube 10-15 Year Timeline

15. CIF21 and CUAHSI CIF21 and EarthCube is still being developed. There is the opportunity to impact implementation through participation. CIF21 dovetail with CUAHSI’s Strategic Plan:  Observation and Synthesis  improving accessibility to observational networks  data discovery and community modeling  Data Access  maintain services for diverse data  develop citation and tracking mechanisms  emerging data types and needs  outreach for standards What are the capabilities that water sciences researchers will need in the future?

16. Where can CI Enhance Partnerships? Connect observing systems Connect to other domains and resources: DataNet; computational facilities; synthesis centers

17. Data Management Plans Long-standing policy states NSF’s expectations with respect to sharing of data and other research products: Grant Conditions: “NSF expects investigators to share with other researchers, at no more than incremental cost and within a reasonable time, the data, samples, physical collections and other supporting materials created or gathered in the course of the work. It also encourages grantees to share software and inventions or otherwise act to make the innovations they embody widely useful and usable.”

18. Data Management Plan  All proposals must include, as a supplementary doc up to 2 pages, a Data Management Plan.  Plan should describe how the proposal will conform to NSF policy on dissemination and sharing of research results.  Plan will be reviewed as part of the intellectual merit and/or broader impacts of the proposal depending on the proposal intent. FastLane will not permit submission of a proposal that is missing a data management plan.

19. What’s Included? o Anticipated data, samples, physical collections, software, curriculum materials, anything produced during the reseach. o Information on analytical standards, metadata, solutions or remedies where these do not exist. o Plans for data/sample access and sharing, including provision for protection of privacy/confidentiality/ security, intellectual property, or other rights, if appropriate. o Plans for re-use, re-distribution, and production of derived data sets. o Plans for archiving/preserving data, samples, and other research products and providing access to others.

20. Data Management Plan Resources http://www.nsf.gov/geo/geo-data-policies/index.jsp Data Policies and Community Standards Templates Review of DMP is an evolving process. More guidance on review will be forthcoming.

21. Opportunities for CUAHSI CIF21: Integration and Partnerships  Take advantage of resources  Wyoming Supercomputing Center  Powell Center  TeraGrid (XD)  DataNets: DataOne, Data Conservancy  Upcoming Competitions  SI2: NSF 11-539 July 18, 2011  EAR Geoinformatics (?): Will be tied to CIF21 and reports from recent Geoinformatics WS Data management plans are an opportunity  Set community standards for peer review  Provide resources for a broad community Articulate your science needs and tools  Be flexible: technology advance outpaces integration into science;  Unanticipated Scientific Discovery is still allowed!

22. Questions?

23. Broad Principles to Lead CIF21 Builds national infrastructure for science and engineering researchers Leverages common methods, approaches, and applications – focus on interoperability Catalyzes other CI investments across NSF  Provide focus for sustainability  Vehicle for coordinating efforts and programs Shared governance; embedded into every directorate and office

24. Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21) Funding (Dollars in Millions) BIOCISEENGGEOMPSSBEOCIOPPIA Total, NSF Data-Enabled Science$3.0$7.0$5.0$7.0$10.9$4.0$10.0$3.0 Community Research Networks 1.0--2.0-3.02.01.00 New Computational Infrastructure 1.09.03.05.09.15.011.0 Access and Connections to Cyberinfrastructure Facilities 1.0 2.0-$5.06.0 Total, CIF21$6.0$16.0$9.0$16.0$20.0$12.0$23.0$4.0$11.0$117.0

25. Technology Innovation: Requires New Paradigms Unprecedented amounts of data collected across planet (by many orders of magnitude)  All sciences  New instruments, sensors, sociological data Sharing data, software, visualizations  Completely new algorithms, methods, tools Real-time access to instruments and data  Performance, interoperability, remote steering  New types of infrastructure for storage, curation, preservation