When describing the process for creating derived data products, the following information should be included in the data documentation or the companion metadata file:
- Description of primary input data and derived data
- Why processing is required
- Data processing steps and assumptions
- Assumptions about primary input data
- Additional input data requirements
- Processing algorithm (e.g., volts to mol fraction, averaging)
- Assumptions and limitations of algorithm
- Describe how algorithm is applied (e.g., manually, using R, IDL)
- How outcome of processing is evaluated
- How problems are identified and rectified
- Tools used to assess outcome
- Conditions under which reprocessing is required
- How uncertainty in processing is assessed
- Provide a numeric estimate of uncertainty
- How processing technique changes over time, if applicable
Bourque, Linda B., Clark, Virginia A. Processing Data: The Survey Example (Quantitative Applications in the Social Sciences), Sage Publications, Inc. (December 14, 2008), ISBN 08056781901