TitleBodyTechnical Expertise RequiredCostAdditional Information
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
Document steps used in data processing

Different types of new data may be created in the course of a project, for instance visualizations, plots, statistical outputs, a new dataset created by integrating multiple datasets, etc. Whenever possible, document your workflow (the process used to clean, analyze and visualize data) noting what data products are created at each step. Depending on the nature of the project, this might be as a computer script, or it may be notes in a text file documenting the process you used (i.e. process metadata). If workflows are preserved along with data products, they can be executed and enable the data product to be reproduced.

Understand the geospatial parameters of multiple data sources

Understand the input geospatial data parameters, including scale, map projection, geographic datum, and resolution, when integrating data from multiple sources. Care should be taken to ensure that the geospatial parameters of the source datasets can be legitimately combined. If working with raster data, consider the data type of the raster cell values as well as if the raster data represent discrete or continuous values. If working with vector data, consider feature representation (e.g., points, polygons, lines). It may be necessary to re-project your source data into one common projection appropriate to your intended analysis. Data product quality degradation or loss of data product utility can result when combining geospatial data that contain incompatible geospatial parameters. Spatial analysis of a dataset created from combining data having considerably different scales or map projections may result in erroneous results.

Document the geospatial parameters of any output dataset derived from combining multiple data products. Include this information in the final data product's metadata as part of the product's provenance or origin.