Difference between revisions of "AQ 2007 10 31 Discussion"
From Earth Science Information Partners (ESIP)
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*What is the best way to determine "best available evidence"? | *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? | **How do we know if a remote sensing product has been verified with ground data and in situations comparable to use? | ||
| + | *How and why might we tag a dataset "bad data"? | ||
| + | ==Use Case== | ||
| + | ===How much NO2 is man made?=== | ||
| + | *How would we provide data to justify the statement, "Man-made emissions of nitrogen oxides dominate total emissions"? | ||
| + | :::See http://www.apis.ac.uk/overview/pollutants/overview_NOx.htm | ||
Revision as of 12:17, October 31, 2007
back to 2007-10-31 Workshop page
Data/tool Decision Tree
- wonder if we could set up table comparing products
- might do by datasource, visualization tool, processing tool, etc.
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?
- How and why might we tag a dataset "bad data"?
Use Case
How much NO2 is man made?
- How would we provide data to justify the statement, "Man-made emissions of nitrogen oxides dominate total emissions"?
