PS Data Quality 2006 04 25

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Four Main Quality Dimensions

  1. instrument accuracy
  2. platform
  3. environmental effects
  4. data processing

Dimensions of each dimension

What words should be used to break down into a second tier ten-scale in each Main Dimension?

How much will it depend on each context of the data collection and use?

One simple set of criteria

science-ready="A"
commercial-ready="C"
education-ready="B"


Use of the Quality Assessments

Is it risk or degree of confidence?

Related to use in making decisions--there the decision maker needs to determine level of risk aversion appropriate--relates to the cost to a business of making a "bad" decision

Maybe we can provide guides-to-use for these assessments

Might be useful even to have a simple five-star system. This might be all that is needed for one category of user--whereas other areas of research might want much more.

Testing

Under what conditions was it tested? Lab, over time, multiple sites and situations


Strategy for getting the assessments entered

Simple assessments can come from the providers themselves

How do we come up with incentives and tools to assure that the provider will/can do this?




Edits to Discussion from March 28, 2006

Objective

Create a common set of data quality metrics across all Federation data products. Data providers can provide measures for their own products. 3rd parties can provide their own ratings. Quality can refer to accuracy, completeness, and consistency. It is not clear how to measure consistency. It is desirable to provide quality assurance.

We would like to create a 1-10 Data quality scale, where:

 1 = no accuracy claimed
10 = fully reliable data that has withstood the test of time

This measure can be applied to any of the quality dimensions:

Quality Dimensions

  1. Sensor/Instrument (well calibrated, stable, checked across instruments, V/V)
  2. Spacecraft (locational and communication accuracy)
  3. Environment Issues (contamination from clouds, rainfall, ground, sea, dirt, etc.)
  4. Data Processing (accuracy of interpolation, algorithms, ancillary source data)

Our Task

Create a 1-10 scale for each dimension. We will work with Federation members to associate a quality description with each value.


Other topics

Quality assurance (someone tags it as valid)
Useful metadata provided?
Instrument Verification and Validation
Data processing
Re-processing tag and notification
input errors and forcings
re-gridding
missing data
Usage issues
High enough resolution?
Valid inference about what is measured
Chain of Custody (for legal use)

Completeness Can we come up with categories of data completeness?

3rd party ratings

NCDC
NCDC Certified data (only states that it is in the archive -- designates as official, not a quality statement)
Dataset docs use FGDC quality section, with different levels of detail
GCMD
DIF records have some minimum required fields to accept
then have a text field to describe quality
ECHO
"measured parameters" from ECS model
QA percent cloud cover; missing pixels;
CLASS/Climate Data Record
Maturity Model approach for data (John Bates application from software maturity)
Level of maturity (five levels of improved treatment)
See CDR Maturity paper
FGDC
Whole section on quality, text only
Testimonials
Peer review

Discussion

Completeness

  • Is this a measure of quality?
Depends on stated offering from the provider; if they claim it is complete and it isn't

Assertions about datasets

We may want some standard for claiming and measuring how valid a claim may be


Additional Questions

  • What common data quality standards can the Federation offer within the Earth Information Exchange?
  • How can we enforce these standards within the Earth Information Exchange?
  • Are there similar ratings for "data services"?

Action

Rob will send advertisement to the whole group for next months meeting.