new challenges in astronomy -...
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New Challenges in Astronomy Dr Alberto ContiSpace Telescope Science Institute
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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
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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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