Step 4: Renovate codebooks

Now we have a profile of they the metadata linkage for a dataset we can start preparing those individual linkage specific codebooks.

Things you will need

Description

After we have evaluated the metadata linkage for a dataset. We will know which codebook and codebook variations to prepare. For each dataset we could potentiall have up to four:

  1. codebook_simple.csv: (Very common) will link to the data via only a single identifer var_name and contain all the metadata fields that were categorized as ‘simple’.

  2. codebook_by_country.csv (Very common) will link to the data via var_name and iso2; it will contain all the metadata fields that were categorized as ‘by_country’

  3. codebook_by_year.csv (Uncommon?) will link to the data via var_name and year; it will contain all the metadata fields that were categorized as ‘by_country’

  4. codebook_by_country.csv (Rare) will link to the data via var_name and strata_id; it will contain all the metadata fields that were categorized as ‘by_country’. Metadata links to data via

Deliverable

For each data set review the metadta linkage evaluation. For each unique linkage that is present in your dataset you will need to prepare the assosiated codebook. The thought process and deliverables for our three example datasets can be seen below. Note these codebooks are from an older template, please use the template provided below.

Important

Step 4 template: 📥 codebook_template.csv

Based on the APS codebook evaluation we saw that all the metadata are categorized as simple; therefor our step -4-codebooks deliverable for this dataset contains one file - codebook_simple.csv

Based on the CNS codebook evaluation we saw:

  • 17 simple fields
  • 2 by_country fields (source, public)

Therefore we need to prepare two codebooks for this dataset (see below).

Based on the SVY codebook evaluation we saw:

  • 15 simple fields
  • 2 by_country fields (source, public, censor)
  • 2 by_strata (var_def, interpretation)

Therefore we need to prepare three codebooks for this dataset (see below).