Difference between revisions of "Question Three"

From Earth Science Information Partners (ESIP)
 
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* Use appropriate metadata standards that include quality data
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* Embed links in metadata to community-supported quality information (see questions [[http://wiki.esipfed.org/index.php/Question_Eight 8]] and [[http://wiki.esipfed.org/index.php/Question_Nine  9]])
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* Include ability to find citations to data in publications to illustrate uses
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* Create tools to compare basic attributes of comparable datasets (see question [[http://wiki.esipfed.org/index.php/Question_Eleven  11]]). I.E. C/NET product comparisons
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* Keep [all] documentation with data. Evolve data models to include all relevant metadata
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* Invest in other quality and impact metrics. For example, scholarly citation metrics
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* Develop tools (such as the DIAL authoring tools)  that allow users to explore appropriate uses
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* Richer quality measurements in metadata
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* Work with/to standards
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* COMMUNITY vetting for quality marking: make data available to the broader community earlier (See #3)

Latest revision as of 16:06, January 7, 2009

Enter your discussion report-out below:

3. How can data providers make it easier to assess the data quality and the appropriate uses for a data set?

  • Use watermarks as a "stamp of approval"
  • "Brand" products (through time)
  • Develop registry of trusted entities. (assessing quality of watermarkers)

  • Use appropriate metadata standards that include quality data
  • Embed links in metadata to community-supported quality information (see questions [8] and [9])
  • Include ability to find citations to data in publications to illustrate uses
  • Create tools to compare basic attributes of comparable datasets (see question [11]). I.E. C/NET product comparisons
  • Keep [all] documentation with data. Evolve data models to include all relevant metadata
  • Invest in other quality and impact metrics. For example, scholarly citation metrics

  • Develop tools (such as the DIAL authoring tools) that allow users to explore appropriate uses
  • Richer quality measurements in metadata
  • Work with/to standards
  • COMMUNITY vetting for quality marking: make data available to the broader community earlier (See #3)