Describe method to create derived data products

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

Additional Information

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

Cite this best practice:

DataONE Best Practices Working Group, DataONE  (July 01, 2010) "Best Practice: Describe method to create derived data products". Accessed through the Data Management Skillbuilding Hub at https://dataoneorg.github.io/Education/bestpractices/describe-method-to on Mar 01, 2024