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Keep it simple and sufficient (do not multiply it unnecessarily)

General Metadata Best Practices. Keep it simple and sufficient (do not multiply it unnecessarily) Make it intuitive and self-explanatory Make it easily discoverable and accessible Make it unobtrusive yet obvious Make it relevant to context Make it available with all data products

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Keep it simple and sufficient (do not multiply it unnecessarily)

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  1. General Metadata Best Practices • Keep it simple and sufficient (do not multiply it unnecessarily) • Make it intuitive and self-explanatory • Make it easily discoverable and accessible • Make it unobtrusive yet obvious • Make it relevant to context • Make it available with all data products • Make it universally applicable and extensible • Treat it as a product • Support appropriate standards (but not slavishly) • Document and promote it

  2. Metadata uses • Mapping source metadata to integrated metadata • Browsing and searching datasets • Assisting the user in selecting and filtering data • Providing method information • Indicating exceptional events • Flagging at the dataset, sample, and observation level • Facilitating interoperability with other data systems

  3. Dataset Discovery

  4. Monitoring Site Exploration

  5. Glossary And Code Key

  6. Mouse-over metadata lookup

  7. Inter-domain “Rosetta Stone”

  8. Exceptional Event Metadata Exceptional event metadata (such as fires) is stored and dynamically associated with data at run time in order to better inform the user about the context of the data. “Bisquit” fire impacting Crater Lake in 2002

  9. IMPROVE Data Advisories IMPROVE Data Advisories document interesting findings from the IMPROVE database such as data anomalies, potential problems, and new uses for the IMPROVE data. These advisories are stored as metadata in the VIEWS database and dynamically associated with data and products. When a user selects data, the systems checks for any advisories relevant to the data selected and attaches them to the output.

  10. Data Advisory Schema The Data Advisory table contains information that allows each advisory to be dynamically associated with (context-relevant to) the data and products that a user requests.

  11. Closing thoughts • Metadata is relevant at several “levels” and in several contexts: • Dataset description • Sample and observation flagging • Names and codes • Data exchange and interoperability protocols (WCS, WMS, WFS, etc) • What is a minimum set of metadata for the air quality community? • Is there an existing standard that completely fits the bill? • How can we design and refine a minimum set for community use? • How could we solicit input during the design of this metadata? • How would we promote and motivate acceptance of this set? • How would this metadata “standard” facilitate interoperability? • Would it be worth the effort?

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