New Challenges in Astronomy -...
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New Challenges in Astronomy Dr Alberto Conti Space Telescope Science Institute Thursday, March 10, 2011
Transcript of New Challenges in Astronomy -...
New Challenges in Astronomy Dr Alberto ContiSpace Telescope Science Institute
Thursday, March 10, 2011
Optimize the science from community-led astrophysics missions and projects. Develop, nurture, and share innovations in space astronomy science operations.
Collaborate on the next generation of space astrophysics programs.
Optical & UVData Archive
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Astronomy Project TimelineA Partial List of Key Astrophysics Facilities
Start date and Probable Duration
HST
Spitzer
Chandra
FUSE
GALEX
GLAST
Kepler
WMAP
JWST
SWIFT
Beyond Einstein
XMM
SOFIA
INTEGRAL
Ares V Flights
Herschel - Planck
WISE
VAO Operations
ALMA
TMT
LSST
PANSTARRS
NVO Development
SDSS
VLT & Gemini Observatories
SIM? TPF?
2000 2005 2010 2015 2020
Thursday, March 10, 2011
Astronomy Project TimelineSTScI Project and Mission Activity
HST
Spitzer
Chandra
FUSE
GALEX
GLAST
Kepler
WMAP
SWIFT
Beyond Einstein
XMM
SOFIA
INTEGRAL
Ares V Flights
Herschel - Planck
WISE
ALMA
TMT
LSST
PANSTARRS
SIM? TPF?
SDSS
VLT & Gemini Observatories
Start date and Probable Duration
LSST
JWST
2000 2005 2010 2015 2020VAO OperationsNVO Development
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Astronomy is changing
Growth over 25 years is a factor of 30 in glass, 3000 in pixels
Detectors follow Moore’s Law
Total data doubles every year
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ComputerScience Biology Economics
Medicine Government Astronomy
Massive amounts of information
e-Science
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ASTRONOMY IS SPECIAL!
No commercial value
Ideal testbed for complex algorithms
Interesting problems
Plenty of data, plenty of dimensions!
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ADAPT OR PERISH
Terraserver, Google Maps, Google Earth & Microsoft Virtual Earth have revolutionized the way we look at our planet
Microsoft’s World Wide Telescope & GoogleSky are starting to revolutionize the way we look at our universe
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New Science Paradigm for Astronomy
Time
Da
ta V
olu
me
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New Science Paradigm:First Iteration
Data Center A
Data Center B
Data Center C
Observatory X
Observatory Y
Few Data Standards, Some Protocols
Past
Observations of small, carefully selected samples of objects in a
narrow wavelength band
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
The Virtual Observatory
2001 .................2008 (2010)
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and meanwhile...
2001 .................2008 (2010)
+Thursday, March 10, 2011
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New Science Paradigm:Second Iteration
Ad-hoc Data Standards, Ad-hoc Protocols Simple Mining Tools
Present
Mission A
Mission B
Mission C
Observatory X
Observatory Y
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New Science Paradigm:Second IterationPr
esent
“Transition may be chaotic”- Alex Szalay
“Astronomical data are now accessible uniformly from federated, distributed, heterogeneous sources, i.e the Virtual Observatory.” - Kirk Borne
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New Science Paradigm:“Science 2.0”Fu
ture?
NASA Data Centers
Observatories
IndividualUsers
Kitchen Sink
MAST @ STScI
Data DiscoveryData Association
Data Dissemination
Metadata
Enable New Science
Standards
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Global Challenges
• Reduce obstacles to Capturing, Organizing, Summarizing, Analyzing, Visualizing, and Curating
• Consider data and algorithms as “the product”
• Adopt semantic technologies to enable automated metadata tagging, clustering and mining
• Transition to the new astronomy
• Sociological issues
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• Infrastructure not available for intensive data mining
• Solutions for handling large datasets are lacking
• Cloud hosting solutions still expensive
‣ Hubble Archive on Amazon $500K+/yr
• Unclear which commercial solutions can fit science needs
Technological Challenges
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• We must partner with other academic disciplines: Computer Science, Statistics, Applied Mathematics
• We must leverage partnerships with industry interested in enabling Science 2.0
• We must learn to be humble and ask for help
• We must remember that we have the greatest datasets in the world (universe really!)
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