Institute for Sustainable Earth and Environmental Software ISEES

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 Sustainability and Adoption Workshop September 10-11, 2013

2. Introductions • Your 140 character twitter intro

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

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

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

7. 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, …)

8. 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

9. 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

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

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

12. 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

13. 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)

14. Strategic planning approach

15. Two tracks Community Engagement, Sustainability, and Governance Workforce Development Stakeholders and community Sustainability Stakeholders and community Knowledge and skills: content gaps Mechanisms for education Strategic Recommendations Structure and Governance

16. Collaborative Space • Document sharing and wiki • https://projects.nceas.ucsb.edu/isees/projects/software/ • Etherpad collaborative editing • https://epad.nceas.ucsb.edu/ • Username/pw • Username: isees • Password: swforscience

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

18. 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

19. 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

20. 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

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

22. 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)

23. 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)

24. 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)

25. Software Lifecycle and Components Workshop • 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

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

27. Functional areas for ISEES • Participants identified 4 functions • Community building • Training and Advocacy • Consulting Services • Infrastructural Services

28. Training and Advocacy • Advocate for the benefit of Open Source • On-site and remote courses on sw development for research sw developers • Develop the policies that incentivize sharing and collaboration (licensing, attribution) • Provide best practices for swdevelopment aimed at scientific community

29. Community Building • Operate community based support services for software • SW dating game -- match science with sw experts --  e.g. dba services, ux services • Support collaboration groups focus on swprojects

30. Consulting Services • Assisting groups in software: • Design and Architecture, Hardening, Maintenance, Preservation • Consultation and mentoring services • licensing, testing as a service, engineering, cost modeling • Certify papers as reproducible

31. Infrastructural services • Software discovery services • Software review and certification program • Provide software use and quality metrics • Actively survey the community

32. Science & Software collaboration • Science-directed hackathon-style working groups • 8-12 member working groups • co-directed by scientist and developer • address one or more software problems that impede a grand challenge science question • Advisory board equally comprised of scientists/developers to select winning proposals • Option for 1-2 developers to continue on problem between working groups

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