Difference between revisions of "AQ 2007 10 31 Discussion"
From Earth Science Information Partners (ESIP)
m (New page: back to Workshop page ---- ==Usage considerations== ===Legal=== *EPA always has to defend its judgments in court *Court needs "preponderance ...) |
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Line 7: | Line 7: | ||
--This is quite different from 0.95% certainty. | --This is quite different from 0.95% certainty. | ||
===Science=== | ===Science=== | ||
+ | *Needs detailed information about sources and models used in "correcting" data | ||
===Education=== | ===Education=== | ||
+ | *Special considerations for "real-time" data | ||
+ | *Special considerations for hiding and introducing complexity | ||
==Data lineage tracking== | ==Data lineage tracking== | ||
− | *How do we track sources of variance within and across datasets throughout the processing chain? | + | *Do we need to coordinate use of conventions, even in readme files, for tracking observations? |
+ | *How do we track sources and magnitude of variance within and across datasets throughout the processing chain? | ||
**Take as an example the case x and y variance are not the same. | **Take as an example the case x and y variance are not the same. | ||
*Can we list sources of variance that must be taken into consideration as we visualize or composite datasets? | *Can we list sources of variance that must be taken into consideration as we visualize or composite datasets? | ||
Line 18: | Line 22: | ||
***interference (NOx) | ***interference (NOx) | ||
==Data quality considerations== | ==Data quality considerations== | ||
+ | *What is the best way to determine "best available evidence"? | ||
+ | **How do we know if a remote sensing product has been verified with ground data and in situations comparable to use? |
Revision as of 11:20, October 31, 2007
Usage considerations
Legal
- EPA always has to defend its judgments in court
- Court needs "preponderance of evidence" or "beyond a reasonable doubt"
--This is quite different from 0.95% certainty.
Science
- Needs detailed information about sources and models used in "correcting" data
Education
- Special considerations for "real-time" data
- Special considerations for hiding and introducing complexity
Data lineage tracking
- Do we need to coordinate use of conventions, even in readme files, for tracking observations?
- How do we track sources and magnitude of variance within and across datasets throughout the processing chain?
- Take as an example the case x and y variance are not the same.
- Can we list sources of variance that must be taken into consideration as we visualize or composite datasets?
- Cloud cover
- Registration issues
- Instrument issues
- resolution
- interference (NOx)
Data quality considerations
- What is the best way to determine "best available evidence"?
- How do we know if a remote sensing product has been verified with ground data and in situations comparable to use?