Information Management in a NonBibliograpic Environment: Scientific Data - PowerPoint PPT Presentation

Title: Information Management in a NonBibliograpic Environment: Scientific Data


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Information Management in aNon-Bibliograpic
Environment Scientific Data

• Joseph A. Hourclé
• 2007-Nov-20
• FLICC Learning_at_Lunch

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About Me
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STEREO Solar TErrestrial RElations Observatory

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The Virtual Solar Observatory

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The Virtual Solar Observatory

• Federated Search of Solar Physics Data
• 14 organizations (currently)
• 4 more organizations being integrated
• 62 instruments
• Hundreds of distinct data collections
• 10s of millions of records
• Terabytes of Data

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The data is growing

• STEREO
• Launched Oct 2006
• Over 1.5 million images _at_ up to 8MB
• Hinode (Sunrise aka Solar-B)
• Launched Sept 2006
• Over 3 million images _at_ up to 8 MB
• SDO
• Scheduled to launch Aug 2008
• 1 image per second _at_ 32 MB
• 1.5TB/day dedicated connection

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Other disciplines have even more data

• NVO US National Virtual Observatory
• LSST (Large Synoptic Survey Telescope)
• Scheduled to start observing in 2012
• 7-10 TB/night, 3.2Gpix images
• 10 PB/yr
• EOS/DIS Earth Observing System/Data Information
  System
• About 2TB/day, per satellite (8?)
• Planned to be 16 PB

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and were not the only one

• Heliospheric
• Magnetospheric
• Radiation Belt
• ITM (upper atmosphere)
• NVO / IVOA nighttime astronomy
• PDS planetary
• EOS earth

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What is Scientific Data?

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How is Scientific Data Gathered?

• Scientist thinks up a problem
• Scientist (and Engineers) create an instrument to
  conduct an investigation
• The instrument collects data via sensors
• Data are calibrated
• Data are written into scientifically useful
  formats
• Data are distributed to the scientists

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But really, what is data?

• There is no formal definition.
• Its as ambiguous as the term book
• Data may be shorthand for
• Data Collection
• Data Series
• Data Set
• Data Product
• Data Granule

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The problem with data

• Every investigation has different data needs
• Each investigation organizes and catalogs the
  data to answer their scientific question
• What is good data for one group may not be
  useful for another
• Because data is being collected continuously,
  there may not be a consistent boundary on one
  granule of data
• Some data is tracked as individual values, and
  only packaged upon request
• Mostly time-series data, not images

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Types of Data Archives

• Instrument Archives
• Maintained by the PI team
• Little or no consideration towards re-use
• Resident Archive
• Maintained by a specific discipline
• Re-use within the given discipline
• Long-Term Archive
• Required for federally funded studies
• Focus on preservation, not use of data

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Active Archives

• Still changing
• May be ingesting from an active mission
• May still be processing their data
• May serve multiple editions or processed states
  of the data
• Final Data in Physical Units typically isnt
  available until one or more years after the
  mission
• Not directly comparable with data from other
  instruments until then

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Isnt this just Knowledge Management?

• There is no knowledge in the raw data
• But there is knowledge in the design of the
  instruments sensors
• What spectral range are the instruments sensitive
  to?
• What are the instruments possible operating
  modes?
• Knowledge of the instruments sensors affect how
  the scientists interpret data
• The scientists have to interpret the results to
  determine the knowledge
• May be reluctant to have others catalog their
  data, as it requires understanding the science

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Multiple Operating ModesFilters on SOHO/EIT
171Å
195Å
284Å
304Å
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Known Sensor Issues SOHO/LASCO
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Knowledge Mgmt, cntd

• We do have Event and Feature Catalogs
• Scientists will record when/where they think
  something interesting is occurring, and share
  with others.

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Data Processing Raw Image (Linear)
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Data Processing Calibrated (Greyscale)
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Data Processing Before Calibration
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Data Processing Best Calibration
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Data ProcessingCCD Aging
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CCD Calibration
195Å
171Å
304Å
284Å
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Higher Level Data
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The Problems

• Cross discipline translation is difficult
• Concepts of what makes data useful differs
  between disciplines
• Different disciplines use different search
  parameters
• VSO time, spectral range, location on sun
• Always looking at the same object
• VHO location of observer, time, spectral range
• Observatories are moving, in situ measurements
• EOS location of object observed
• NVO direction of pointing (assumed from earth)

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Problems, cntd.

• Even when there is agreement, there are still
  problems
• Which time is important?
• Start time?
• Average time?
• Spacecraft time?
• Which coordinate system is used?

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Problems, still cntd

• Each discipline is working on solutions within
  their field
• Build systems that suit the needs of their
  community
• Each discipline has different first class data
• Currently working on metadata standards so data
  can be discovered and used by other disciplines
• SPASE MMI GEON
• Some work on ontologies to help with discovery
  and use
• VSTO SWEET GEON SESDI

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Lots of Permutations
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I know what youre thinking
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And it mostly works
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How does this affect libraries?

• The library is a changing organism
• Data is relatively unanalyzed in LIS
• Data connects to bibliographic records, and
  visa-versa
• What data was used in this journal article?
• Where can I get documentation on using this data?
• Has anyone published anything using this data?
• Data connects to other data
• What other instruments observed a given event?
• Is there an alternate version that better meets
  my needs?

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Theres funding for research

• NSF
• CDI Cyber-Enabled Discovery and Innovation
• INTEROP Community-based Data Interoperability
  Networks
• IIS Information and Intelligent Systems
• DataNet Sustainable Digital Data Preservation
  and Access Network Partners
• NASA
• AISR Advanced Info. Systems Research
• ACCESS Advancing Collaborative Connections for
  Earth Science Access

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Sunspot on 15 July 2002 from the Swedish 1-m
Solar Telescope on La Palma
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http//virtualsolar.org/ http//stereo.gsfc.nasa.
gov

• joseph.a.hourcle_at_nasa.gov

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