Institute for Sustainable Earth and Environmental Software

ISEESMatthew B. Jones

National Center for Ecological Analysis and Synthesis (NCEAS)

University of California Santa Barbara

ISEES Science Drivers WorkshopMarch 11-12, 2013

Science and Synthesis

• Role of synthesis in advancing science• Merger of synthesis with experimental and

observational science

Ocean Health Index (OHI)Oc

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Pace of Shifting Climate in Marine and Terrestrial Ecosystems

Burrows et al. 2011. Science 334:652-655“The velocity of climate change is two to seven

times faster in the ocean than on land in the sub-Arctic and within 15° of the equator...”

Synthesis over time

• Jackson et al., Science 2001

Software in the science lifecycle

From Reichman, Jones, and Schildhauer; doi:10.1126/science.1197962

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, …)

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

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

ISEES Structure

• Community driven initiative– Provide mechanisms to empower the community– Model after synthesis centers

• Prioritize based on science drivers• Link to community initiatives such as ESIP• Enable a new generation of open, reproducible

science

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)

Strategic planning approach

Science Drivers

• Goal: Explore science drivers for ISEES– (some drivers, not *the* drivers)

• Connect the science drivers to software needs

• Envision role of a software institute in enabling science

9:00 am – The 2-day process

Defining the Grand Challenge Questions

Monday

Scientists’ Needs and Benefits

Workflow Software Needs

Defining the Analytical Workflow to Answer

the Questions

Tuesday

• Question• Problem statement/background• How answer benefits science• How answer benefits society• 3-6 references

• Workflow (WF) diagram• Data needs• Analysis/viz. needs• Collaboration needs

• List of software needs• WF-SW Commonalities• WF-SW Differences

• What does ISEES look like?

• Workforce needs• Community needs• Community benefits

Introductions

• Name • Affiliation• Area(a) of expertise and interest• Favorite vacation spot

Questions?

• http://isees.nceas.ucsb.edu/

• http://www.nceas.ucsb.edu/ecoinfo/