Step 1: Data gap and quality analysis

Goal: Generate insights from the data gaps and quality.

Situation: You have collected and processed a lot of data. In doing so, you have realised where data gaps existed and what the quality of the data is. This situation and your insights on it have an effect on the interpretation of the results, and should also be communicated (in the UCA report).

Approach: Study the quality of the data and evaluate data gaps.

Data quality assessment

  1. Copy the data quality matrix template.
  2. Critically reflect on the data quality and add your observations on all four data quality dimensions of reliability, completeness, temporal correlation, spatial correlation.
  3. Fill in the table with the codes for high, medium, low, for the respective levels.
    • If you are using the UCA online report form, you can use the “”span data-color”” codes to generate the colours.
    • If you are using your own way of reporting, simply fill the matrix with the levels of high, medium, low and mark the colours manually.
  4. Once done, copy the table into field 21 of the online report form, or simply into your report. (See explanation in Online Report > How to copy a table from a spreadsheet into the report)
  5. Write a few paragraphs summarising the data quality matrix and add them to field 22 of the online report form, or your report.

Data gap assessment

  1. Summarise in a couple of sentences for which lifecycle stages or materials you have found data and for which not.
  2. Write a number of sentences on how you closed data gaps: You can describe which sources, assumptions and calculations were used to downscale data or approximate data to close the gaps.
  3. If you wish, you can also add some reflections on what kind of other data would be beneficial to have.
  4. Add this text to field 23 of the UCA online report form or your own report.