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Talk given at the National Academy of Sciences about the current astronomical landscape and some of the issues the virtual observatory is facing

Talk given at the National Academy of Sciences about the current astronomical landscape and some of the issues the virtual observatory is facing

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  • \n
  • Here are the 3 primary goals the institute’s CMO strives to achieve.\n
  • You clearly know the landscape of astronomy missions and facilities on the ground and in space is quite diverse and holds promise for many exciting discoveries. Our aim is to offer to the community the use our scientific and technical experiences to help minimiize duplication of effort, help avoid known operational pitfalls. But we, as members of this same community, are also keenly interested in identifying and collaborating in future missions that will carry astrophysics forward in a number of areas.\n
  • These are the subset of those missions that we are or will be playing a role in. Obviously some, like HST and JWST, we play a key role. Others we play an important supporting role by carrying out a specific operations task that is integrated with an external science operations center or team.\n
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National Academy of Sciences National Academy of Sciences Presentation Transcript

  • New Challenges in Astronomy Dr Alberto Conti Space Telescope Science
  • Optical & UV Data ArchiveOptimize the science from community-ledastrophysics missions and projects.Develop, nurture, and share innovations inspace astronomy science operations.Collaborate on the next generation of spaceastrophysics programs.
  • Astronomy Project Timeline A Partial List of Key Astrophysics Facilities Ares V Flights Beyond Einstein INTEGRAL WISE JWST SWIFT SIM? TPF?WMAP Herschel - Planck Kepler GLAST GALEXFUSEXMMChandraSpitzerHST SOFIASDSSVLT & Gemini Observatories PANSTARRS LSST TMT ALMA NVO Development VAO Operations2000 2005 2010 2015 2020 Start date and Probable Duration
  • Astronomy Project Timeline STScI Project and Mission Activity Ares V Flights Beyond Einstein INTEGRAL WISE JWST SWIFT SIM? TPF?WMAP Herschel - Planck Kepler GLAST GALEXFUSEXMMChandraSpitzerHST SOFIASDSSVLT & Gemini Observatories PANSTARRS LSST TMT ALMA NVO Development VAO Operations2000 2005 2010 2015 2020 Start date and Probable Duration
  • Astronomy is changing Growth over 25years is a factor of30 in glass, 3000 inpixels Detectors followMoore’s Law Total data doublesevery year
  • Computer Biology Economics ScienceMedicine Government Astronomy Massive amounts of information
  • e-SComputer Science Biology Economics c ienMedicine Government ce Astronomy Massive amounts of information
  • e-SComputer Science Biology Economics c ienMedicine Government ce Astronomy Massive amounts of information
  • ASTRONOMY IS SPECIAL!No commercial valueIdeal testbed forcomplex algorithmsInteresting problemsPlenty of data, plentyof dimensions!
  • ADAPT OR PERISHTerraserver, Google Maps,Google Earth & MicrosoftVirtual Earth haverevolutionized the way welook at our planetMicrosoft’s World WideTelescope & GoogleSkyare starting torevolutionize the way welook at our universe
  • Data Volume Time New Science Paradigm for Astronomy
  • stPa New Science Paradigm: First Iteration Few Data Standards, Some Protocols Data Center A Data Center B Observatory X Data Center C Observatory Y
  • stPa New Science Paradigm: First Iteration Few Data Standards, Some Protocols Observations of small, carefully selected samples of objects in a narrow wavelength band
  • The Virtual Observatory
  • The Virtual Observatory 2001NVO
senior
personnel:Charles
Alcock,
University
of
Pennsylvania
Kirk
Borne,
Astronomical
Data
Center/Raytheon
Tim
Cornwell,
NSF
NaEonal
Radio
Astronomy
Observatory
David
De
Young,
NSF
NaEonal
OpEcal
Astronomy
Observatory
Giuseppina
Fabbiano,
Smithsonian
Astrophysical
Observatory
Alyssa
Goodman,
Harvard
University
Jim
Gray,
Microso.
Research
Robert
Hanisch,
Space
Telescope
Science
InsEtute
George
Helou,
NASA
Infrared
Processing
and
Analysis
Center
Stephen
Kent,
Fermilab
Carl
Kesselman,
University
of
Southern
California
Miron
Livny,
University
of
Wisconsin,
Madison
Carol
Lonsdale,
NASA
Infrared
Processing
and
Analysis
Center
Tom
McGlynn,
GSFC/HEASARC/USRA
Andrew
Moore,
Carnegie
Mellon
University
Reagan
Moore,
San
Diego
Supercomputer
Center/UCSD
Jeff
Pier,
United
States
Naval
Observatory,
Flagstaff
StaEon
Ray
Plante,
University
of
Illinois,
Urbana‐Champaign
Thomas
Prince,
California
InsEtute
of
Technology
Ethan
Schreier,
Johns
Hopkins
University/STScI
Nicholas
White,
NASA
Goddard
Space
Flight
Center
Roy
Williams,
California
InsEtute
of
Technology
  • The Virtual Observatory 2001
  • The Virtual Observatory 2001 ................. 2008 (2010)
  • The Virtual Observatory 2001 ................. 2008 (2010)
  • 2001 ................. 2008 (2010) and meanwhile... +
  • New Science Paradigm: t n se e Second IterationPr Ad-hoc Data Standards, Ad-hoc Protocols Simple Mining Tools Mission A Mission B Observatory X Mission C Observatory Y
  • New Science Paradigm: t n se e Second IterationPr Ad-hoc Data Standards, Ad-hoc Protocols Simple Mining Tools Mission A Mission B Observatory X Mission C Observatory Y
  • New Science Paradigm: t n se e Second IterationPr
  • New Science Paradigm: t n se e Second IterationPr “Transition may be chaotic”- Alex Szalay “Astronomical data are now accessible uniformly from federated, distributed, heterogeneous sources, i.e the Virtual Observatory.” - Kirk Borne
  • ? tu re New Science Paradigm: “Science 2.0”Fu Individual Users MAST @ STScI Observatories Kitchen Sink NASA Data Centers
  • ? tu re New Science Paradigm: “Science 2.0”Fu Standards Individual Metadata Users MAST @ STScI Data Discovery Data Association Observatories Data Dissemination Kitchen Sink NASA Data Centers Enable New Science
  • Global Challenges• Reduce obstacles to Capturing, Organizing, Summarizing, Analyzing,Visualizing, and Curating• Consider data and algorithms as “the product”• Adopt semantic technologiesclustering and automated metadata tagging, to enable mining• Transition to the new astronomy • Sociological issues
  • Technological Challenges • 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
  • • 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!)