Wolfram Data Summit: New Frontiers in Astronomy
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What are the challenges facing astronomy? How can astronomy cope with the changing landscape for both data and collaborations? Here I tried to frame the problem and give some possible answers to what astronomers and others needs to address.
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Wolfram Data Summit: New Frontiers in Astronomy
- 1. New Frontiers in Astronomy Dr Alberto Conti Space Telescope Science Institute
- 2. • Visible – Hubble Space Telescope • Gamma rays - Compton Gamma Ray Obs. • X-rays - Chandra X-ray Observatory April 2006 • Infrared - Spitzer Space Telescope
- 3. Optical & UV Data Archive 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.
- 4. 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 GALEX FUSE XMM Chandra Spitzer HST SOFIA SDSS VLT & Gemini Observatories PANSTARRS LSST TMT ALMA NVO Development NVO Operations 2000 2005 2010 2015 2020 Start date and Probable Duration
- 5. Astronomy Project Timeline STScI Project and Mission Activity Ares V Flights Beyond Einstein INTEGRAL WISE JWST SWIFT SIM? TPF? WMAP Herschel - Planck Kepler GLAST GALEX FUSE XMM Chandra Spitzer HST SOFIA SDSS VLT & Gemini Observatories PANSTARRS LSST TMT ALMA NVO Development NVO Operations 2000 2005 2010 2015 2020 Start date and Probable Duration
- 6. Space is big! For one picture you need a 2 Trillion pixels camera! Challenges for the Future
- 7. Monochrome : 4 Terabytes or 5% of the Library of Congress Challenges for the Future
- 8. Color: 100 Terabytes or the 21% more than the entire Library of Congress Challenges for the Future
- 9. Time: 10 Petabytes or 120 times the entire Library of Congress Challenges for the Future
- 10. New analysis & visualization tools are required Challenges for the Future
- 11. Astronomy is changing Detectors follow Moore’s Law Total data doubles every year Growth over 25 years is a factor of 30 in glass, 3000 in pixels
- 12. Computer Biology Economics Science Medicine Government Astronomy Massive amounts of information
- 13. e-S Computer Science Biology Economics c ien Medicine c Government e Astronomy Massive amounts of information
- 14. Data Volume Time New Science Paradigm for Astronomy
- 15. New Paradigm Issues • Moving data around is hard • Extracting knowledge is hard • Complex, difficult to use • Hard for user to publish their own data • Many distributed services are unreliable
- 16. ASTRONOMY IS SPECIAL! No commercial value Ideal testbed for complex algorithms Interesting problems Plenty of data
- 17. ADAPT OR PERISH Google Earth, Microsoft Virtual Earth have revolutionized the way we look at our planet We need a new synergistic approach to the challenge of bringing the universe to our desktops
- 18. New Science Paradigm: First Iteration Few Data Standards, Some Protocols Mission A Mission B Observatory X Mission C Observatory Y
- 19. New Science Paradigm: Second Iteration Data Standards, Protocols Simple Mining Tools Mission A Metadata Mission B Observatory X Mission C Observatory Y
- 20. New Science Paradigm: Science 2.0 Individual Users MAST @ STScI Intʼl Data Centers Kitchen Sink NASA Data Centers
- 21. 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
- 22. Technological Challenges • Infrastructure not available for intensive data mining • Solutions for handling large datasets are lacking • Cloud hosting solutions still expensive • Unclear if commercial solutions can fit science needs
- 23. • We must partner with other academic disciplines: Computer Science, Statistics, ... • 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!)