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TypeVideo Recording
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Year2021
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Author(s)
Aristide Athanassiadis and Carolin Bellstedt -
LicenseCC BY 4.0
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URL
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ID
994528
Insights from a Data Gap Analysis (Module 8) - Online course Sector-Wide Circularity Assessment
Outline of the video
- Last part of insights: data quality.
- You need to know and report how reliable your data and insights are.
- Evaluate your data quality with the data quality matrix
- Use the data quality matrix with the lifecycle stages (LCS) and the 4 dimensions for data quality.
- Under the table template there are the criteria or score points for the respective dimensions that need to be applied to the cells to determine high, medium and low.
- You can either only color code the cells with the criteria, or also add notes into the fields. If you have longer notes or explanations, then those can also be added under the table in your report.
- To color code the fields for the report, within a cell (can be any cell, with or without other text content), insert the respective code, e.g. <span data-color="red"></span>, where “red” stands for low.
- See this example of what the filled matrix could look like in the spreadsheet and what it will look like in an example report. It is described in the FAQ document how to add the table to the report.
- You then need to add a couple of sentences describing the data quality matrix.
- Summarise your data gaps
- Instead of using the entire data gap matrix, you should summarise in a couple of sentences for which LCS or materials you have found data and where you have gaps. Here is where you can also state that you downscaled or approximated data.
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