1. Institute for Sustainable Earth and Environmental Software ISEES Matthew B. Jones National Center for Ecological Analysis and Synthesis (NCEAS) University of California Santa Barbara ISEES Software Lifecycle and Components Workshop August 13-14, 2013

3. Science and Synthesis Synthesis critical to advancing science Merger of synthesis with experimental and observational science

4. Ocean Health Index (OHI) Ocean Health Index Halpern et al. 2012

5. Software in the science lifecycle From Reichman, Jones, and Schildhauer; doi:10.1126/science.1197962

6. Software for the Earth, Life, and Environmental Sciences Statistical analysis – e.g., R, SAS, Matlab, Systat, Excel, etc. One-off models (by students, faculty, etc.) Custom analytics (e.g., Primer, MetaWin, MaxEnt) Modeling frameworks (e.g., ROMS) Community models (e.g., Century, Community Climate Model) Workflows (Kepler, VisTrails, …) Computing engines (e.g., Sun Grid Engine, Amazon ECS) Data management (DataONE, Metacat, DataUp) Service computing (Blast, WMS, WFS, …)

7. Software challenges Wide range of software types Code Complexity and Quality Reproducibility Systems integration Development and maintenance are labor intensive – NSF not set up for infrastructure/maintenance Software lifetime long compared to hardware Under-appreciated value

8. ISEES Vision Massively accelerate science – (Earth, environmental, and life science) – Enable collaboration and integration across disciplines – Invent, develop, integrate, mature, and sustain software used throughout the scientific lifecycle

9. Determining needs What needs to be improved? What challenges do we face? How do we solve these?

10. Any solution must… Provide value to participants in their reputation economy Enable participants, not compete with them

11. Can an Institute build it “for them”? No. Must empower community – Scaling/leverage – Creativity – Knowledge of domain Community driven initiative – Model after synthesis centers – Link to community initiatives such as ESIP

12. ISEES Steering Committee Matthew Jones (Cyberinfrastructure) Lee Allison (Geology) Daniel Ames (Hydrology) Bruce Caron (Collaboration) Scott Collins (Ecology) Patricia Cruse (Library) Peter Fox (CI & Semantics) Stephanie Hampton (Ecology) Chris Mattmann (JPL; Apache) Carol Meyer (ESIP Community) William Michener (DataONE) James Regetz (Analytics) Mark Schildhauer (Semantics)

13. Strategic planning approach

14. ISEES Science Drivers Workshop Outcomes – Science challenges limited by software – Functional areas for ISEES Burrows et al. 2011. Science 334:652-655

15. Fresh water availability Ecosystems Human society Water dimension Biological dimension Human dimension Mean Extremes Uncertainty Mean Extremes Uncertainty Mean Extremes Uncertainty Time Allocation Now Visualization Scenario prescription Data resources CUAHSI HIS World water online GEOSS DataONE NASA/ESA/other NEON EarthCube NSW/WMO/other CoCoRaHS Water managers Army Corps Social media Data types Precipitation Atmos. H 2 O Groundwater Reservoir storage River discharge Water quality Soil moisture Other climate LC/LU Built infrastructure Economic Population Ag/irrigation Sap flux/tower ET Human use Physical hydrology New data initiatives Data management Selection Provenance Rectification Scenario support Simulation Historical Social science Earth system models (CSDMS) CESM ESMICs Data fusion Spatial statistics Assimilation Data ingestion Experimentation Feedback analysis Community input and refinement Theory Algorithms Parameterizations How will coupled human and biophysical systems shape and be shaped by water availability?

16. Sources Transport Recipient Systems Resistor Output Visualization Scenarios Decision-Support tool Climate change (model output) Hydrological modifications Population change (scenarios) Land use and cover change (models, observations) Archive, provenance, other considerations Q: What are the controls, impacts, and societal responses to atmosphere–land–water transfer of pollutants, and how will they change under multiple, global-change stressors?

17. Modularity: main program with modules (off/on in parameter file) Flexible I/O: OPeNDAP (Open-source Project for Network Data Access protocol); Storage: flexible output (netcdf, ASCII formats) and data archive system Existing pollutant transport models CMAQ annual deposition Community Modeling and Analysis System (CMAS) Center Community Modeling and Analysis System (CMAS) Center SPARROW water quality model USGS NASA models of aerosol movement SMS and Delta3D for sediment transports CMS for CDOM transport and oil-spills Landscape and habitat models (USGS, WRI) Software Needs for Data & Model Output Synthesis Perturbations of IC (climate and land-use scenarios) New transport models: Coupled atmospheric-ocean transport models - High Performance Computing with multi-processors and MPI capabilities - multi-scale nesting capabilities - hind-cast and near-real time capabilities - stochastic capabilities & ensemble simulations to formulate uncertainties Output & Visualization Needs user interface, interactive scenarios connectivity module linking sources to recipients: where the pollution comes from? Matlab 2 & 3D animations R - statistical package

18. Spatially and temporally predict carbon storage & flux globally at 1km scales to 2300

19. What can ISEES do for you? Computation training for early career and mid and senior scientists (14) Assimilation and QA/QC tools for heterogeneous data (13) Provide a collaborative environment for ecologists, computing scientists, social scientists, etc. (10) Develop dynamic, flexible visualization tools (9) Support for software maintenance and sustainability, including software building blocks (e.g., modules) (9)

20. What can ISEES do for you? Improved tools for capturing decisions and workflows in collaborative research projects (6) Software discovery: One-stop shopping for finding and characterizing software and models -- focus on users (6) Provide consultants, collaborators for software, CS, for researchers (6) Community hub for standards convergence (4) Facilitate merging of disparate software tools (3) Develop user-friendly interfaces to existing models (3) Provide a framework for multiscale, coupled modeling systems (2)

21. What can ISEES do for you? Make high performance computing available to the average ecologist and environmental scientist (2) Software to help with uncertainty and error propagation in spatial models (2) Provide web-based software services, i.e. ability to run analyses on ISEES servers via accessible interfaces (2) Software vetting (check software being developed in-house) (1) Help me contribute to community software (1) Taxonomy scrubbing software (1) Improved model intercomparison (1)

22. Software Lifecycle and Components Goal: Envision a model for ISEES that enables efficient, reproducible, scalable, and impactful environmental science – Identify *functions* that ISEES would be ideally suited to perform or coordinate – Provide recommendations to the ISEES steering committee for our strategic plan Contribute to a paper outlining this vision for ISEES Stimulate amazing and fun discussions here and later about software in science

23. ISEES Software lifecycle model Figure by M. B. Jones, NCEAS

24. The 2-day process Lifecycle Analysis Tuesday Create and Refine Logic Models Define Mechanisms and Resources Define Functions and Services What problems to be solved? What functions and services provided? What mechanisms used? What resources needed? Wednesday Strategic Plan Recommendations

25. Collaborative Space Document sharing and wiki – https://projects.nceas.ucsb.edu/isees/projects/soft ware/ https://projects.nceas.ucsb.edu/isees/projects/soft ware/ Etherpad collaborative editing – https://epad.nceas.ucsb.edu/ https://epad.nceas.ucsb.edu/ See whiteboard for username/pw

26. Introductions Name Area(a) of expertise and interest Your professional mentor/hero

27. Questions? http://isees.nceas.ucsb.edu/ http://www.nceas.ucsb.edu/ecoinfo/

28. Challenge Statement: Earth and environmental scientists face critical society-relevant research questions that increasingly demand interoperability of robust data- and analysis-relevant software components that together span many spatial scales, temporal scales, and science domains. However, absent a collective vision and support infrastructure, most existing scientific software tools are the product of ad hoc, parochial, short-term development efforts, defeating our ability to leverage the full power of modern computing capabilities.

29. Working Groups and Activities Science Cluster (March 2013) – Collins and Michener – Collates and articulates grand challenges within earth observational sciences that focus and drive ISEES’ software activities and define exemplary collaborative science activities supporting detailed requirements analysis.

30. Working Groups and Activities ESIP Town Hall (July 2013) – Communicates results to the broader community and solicit feedback used to inform the final Strategic Plan.

31. Working Groups and Activities Software Cluster (August 2013) – Mattman, Fox, Schildhauer, Jones – Analyzes requirements for scientific software and proposes approaches for ISEES to address these via improvements across the full software lifecycle.

32. Working Groups and Activities Sustainability & Adoption Cluster (September 2013) – Meyer, Caron, Ames, Hampton, Cruse, Allison – Examines sustainability and governance challenges, and proposes models for engaging the research community, governing ISEES, and developing an effective workforce that can sustain the portfolio of science software curated through ISEES.