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Institute for Sustainable Earth and Environmental Software ISEES

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. Science and Synthesis.

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Institute for Sustainable Earth and Environmental Software ISEES

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  1. Institute for Sustainable Earth and Environmental SoftwareISEES 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

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

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

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

  5. 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, …)

  6. 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

  7. ISEES Vision • Massively accelerate science • (Earth, environmental, and life science) • Enable collaboration and integration across disciplines • Invent, develop, integrate, mature, and sustainsoftware • used throughout the scientific lifecycle

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

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

  10. 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

  11. 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)

  12. Strategic planning approach

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

  14. How will coupled human and biophysical systems shape and be shaped by water availability? Community input and refinement Theory Algorithms Parameterizations Experimentation Feedback analysis • Data fusion • Spatial statistics • Assimilation • Earth system models (CSDMS) • CESM • ESMICs Visualization Fresh water availability New data initiatives Mean Mean Mean Extremes Extremes Extremes • Data management • Selection • Provenance • Rectification • Scenario support • Simulation • Historical • Social science Water dimension Uncertainty Uncertainty Uncertainty Ecosystems Allocation Data ingestion • Data resources • CUAHSI HIS • World water online • GEOSS • DataONE • NASA/ESA/other • NEON • EarthCube • NSW/WMO/other • CoCoRaHS • Water managers • Army Corps • Social media Biological dimension Scenario prescription Human society • Data types • Precipitation • Atmos. H2O • 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 Human dimension Time Now

  15. 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? Recipient Systems Sources Population change (scenarios) Land use and cover change (models, observations) Resistor Transport Output Visualization Scenarios Decision-Support tool Climate change (model output) Hydrological modifications Archive, provenance, other considerations

  16. Software Needs for Data & Model Output Synthesis • 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 • 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) 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? • Matlab2 & 3D animations • R - statistical package

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

  18. 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)

  19. 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)

  20. 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)

  21. 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

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

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

  24. Collaborative Space • Document sharing and wiki • https://projects.nceas.ucsb.edu/isees/projects/software/ • Etherpad collaborative editing • https://epad.nceas.ucsb.edu/ • See whiteboard for username/pw

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

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

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