The Initiative in Innovative Computing at Harvard Alyssa A. Goodman Professor of Astronomy & Founding Director of the Initiative in Innovative Computing,

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Presentation transcript:

The Initiative in Innovative Computing at Harvard Alyssa A. Goodman Professor of Astronomy & Founding Director of the Initiative in Innovative Computing, Harvard University Scholar-in-Residence, WGBH Boston

from the 2009 IIC Report...

Where did IIC come from, and go? Short Version Response to Harvard’s “expansion” in Science, and into Allston. See IIC Whitepaper (2004) & Task Force on Science & Technology report (2005) for more.Whitepaper report Long Version (see the News on Allston & Harvard) Current Status Part of Harvard’s New School of Engineering and Applied Science

IIC 2010: Part of Harvard’s New Engineering School

Filling the “Gap” between Science and Computer Science Increasingly, core problems in science require computational solution Typically hire/“home grow” computationalists, but often lack the expertise or funding to go beyond the immediate pressing need Focused on finding elegant solutions to basic computer science challenges Often see specific, “applied” problems as outside their interests Scientific disciplinesComputer Science departments

Continuum “Pure” Discipline Science (e.g. Galileo) “Pure” Computer Science (e.g. Turing) “Computational Science” Missing at Most Universities

Where are the optimal “IIC” problems? Low High Computer Science Payoff Domain Science Payoff Low HIgh “Never Mind” Computer Science Departme nt Science Departments CS Departments What is the right shape for that boundary?

IIC “Whitepaper” 2004 IIC Report 2009

IIC Symposium 2007

Calculations Relative Strengths Pattern Recognition Creativity

Fiction Truth

Data Reduction Data Display Context (e.g. journals + online data) Simulation Design Statistics Design Data Exploration (Visualization) Yellow Arrow

How do stars form in our Galaxy today? What does the wiring diagram of the human brain look like? How should we model blood flow in the human body from atomic to physiological scales? How is science best communicated? How should we use technology in teaching? What’s “Dark Energy”? What are the earliest structures in the Universe? What’s “Dark Energy”? What are the earliest structures in the Universe?

IIC Report 2009: All 100+ pages available at this workshop’s website IIC Report 2009: All 100+ pages available at this workshop’s website

One example...

Astronomical Medicine/3D Results are fantastic– but not instant! Seamless Astronomy ( )

Alyssa Goodman (IIC/CfA/FAS) Michael Halle (IIC/SPL/HMS) Ron Kikinis (SPL/HMS) Douglas Alan (IIC) Michelle Borkin (FAS/IIC) Jens Kauffmann (CfA/IIC) Erik Rosolowsky (CfA/UBC Okanagan) Nick Holliman (U. Durham) z Astronomical Medicine

The Astronomical Medicine Story “Viz has failed the scientific community…” Computer Scientist Astronomer Unsuspecting Undergrad +Nick Holliman (CS, 3D expert) +Doug Alan (S/W Engineer) +Jens Kauffmann (postdoc) +Erik Rosolowsky (postdoc) +...

COMPLETE=COordinated Molecular Probe Line Exinction Thermal Emission mm peak (Enoch et al. 2006) sub-mm peak (Hatchell et al. 2005, Kirk et al. 2006) 13 CO (Ridge et al. 2006) mid-IR IRAC composite from c2d data (Foster, Laakso, Ridge, et al. in prep.) Optical image (Barnard 1927)

“Keith”“Perseus” “Astronomical Medicine” “z” is depth into head“z” is line-of-sight velocity (This kind of “series of 2D slices view” is known in the Viz as“the grand tour”)

mm peak (Enoch et al. 2006) sub-mm peak (Hatchell et al. 2005, Kirk et al. 2006) 13 CO (Ridge et al. 2006) mid-IR IRAC composite from c2d data (Foster, Laakso, Ridge, et al. in prep.) Optical image (Barnard 1927) Perseus

3D Viz made with VolView Perseus

23 Some of What We’ve Learned... Cores nest in coccoons (Kauffmann et al. 2009) Gravity Matters (Goodman et al. 2009) Tripled Outflows (Borkin et al. 2008,9) Shells Rule (Arce et al. 2009)

New ways to share insight “3D PDF” Goodman et al. Nature, 2009

Secret truths I learned from AstroMed at IIC 1. The story about the hammer & the screw is a cliché, but it’s true. Don’t use “more” software than you must. (e.g. 3DSlicer/Osirix/VolView/AplPy/S2PLOT/custom apps) 2. Smart hackers rule. Software engineering is great when you have the money & time. 3. Distribution is key. There’s too much great S/W no one knows about.

My “advice” re:IIC-like Enterprises

“Seamless Astronomy” is collaboration amongst many researchers at CfA, MSR, Princeton, STScI, NYU, RPI, and UCLA, and it is supported by NASA, NSF and Microsoft External Research. What I’m doing now...

Seamless Astronomy Mockup based on work of Eli Bressert, excerpted from NASA AISRP proposal by Goodman, Muench, Christian, Conti, Kurtz, Burke, Accomazzi, McGuinness, Hendler & Wong, 2008 Semantic Search Data Viewer (e.g. WWT) Literature Viewer Archive Browser Info Viz for Search Results 3D Viewer... Sim-based Analytics

User Group Markup Tool Use Cases Chandra, TSC, Gen. by User Group (incl. AG’s shells project), MAST-oriented Discourse Ontology Workflow Ontology (e.g. myepxeriment) AA Astronomy Ontologies data (pragmatic, obsv. -oriented) concepts (astrophysical) math/statisti cs ADS PDFs astrometry.net GSky & WWT E1E1 Astronavigator (primarily a mechanism for linking tools, also ultimately a limited “workbench” providing provenenance) FF Bibliographic Ontology (enables relationships between holdings as in a library; e.g. Dublin Core) BB 1 2 “Semantic” Search (using ontologies via facets and/or other semantic approaches) 4 DD CC graph of interconnections3E2E2 5 Early Science Demonstrations Existing “VO” Tools The guts of “Seamless Astronomy”

Touching Insight The Scientists’ Discovery Room movie courtesy Daniel Wigdor, equipment now in Chia Shen’s SDR lab at SEAS