CESSDA Archive

Quality check

Notes

Austria (AUSSDA)

YES

• We compare data and documentation (including checks if value labels and variable names match in dataset and documentation);
• We check for completeness of data and labels and we conduct plausibility checks.

Czech Republic (CSDA)

YES

Only a basic quality check (CSDA, 2016) is performed:

• Check that variables in the dataset correspond to a questionnaire;
• Basic control of frequencies of variables and values of variables (to find values that are out of given range).
• A check of variable and value labels to see whether they correspond to labels in a questionnaire.

No elaborate analysis of data quality (like checking construct validity, record check studies etc.) is done.

Greece (So.Da.Net)

YES

Basic quality checks to ensure the completeness and the understanding of any deposited data, as follows:

• Dataset dimension checks: the number of cases and variables are checked against the documentation;
• Metadata checks: all variables should have variable labels and all categorical variables should have value labels / the dataset must be comprehensible in association with the documentation given to users;
• Data validity checks:
  • All categorical variables must be checked for out-of-range values/wild codes;
  • Possible interval variables must be checked for improbable or impossible value.

Netherlands (DANS)

YES

DANS performs data quality checks of the deposited data and metadata. DANS provides specific instructions for depositing social science data on their website, including an overview of the data requirements which will be checked during the process. See the 'Depositing information' (DANS, n.d.b) and a detailed list of the data quality checks (DANS, n.d.c).

Norway (NSD)

YES

All data that are deposited are reviewed and processed, for instance, all data are checked with respect to anonymity. See the information on the website of the Norwegian Center for Research Data (NSD, n.d.a).

Slovenia (ADP)

YES

Detailed quality checks to ensure the completeness and the understanding of any deposited data and documentation, as follows:

• Dataset dimension checks: the number of cases and variables are checked against the documentation;
• Metadata checks: all variables should have variable labels and all categorical variables should have value labels / the dataset must be comprehensible in association with the documentation given to users;
• Data validity checks:
  • All categorical variables must be checked for out-of-range values/wild codes;
  • Possible interval variables must be checked for improbable or impossible values - dataset being checked for consistency with/against published results (e.g. report, journal article…);
  • Research material being checked for legal consistency (e.g. GDPR, IPR).

Sweden (SND)

NO

SND controls that the data is readable and that all data is deposited. No quality control is performed on the content apart from what is provided as metadata.

Switzerland (FORS)

YES

FORS performs quality assurance routine checks for completeness, integrity, comprehensibility, and validation of the data files:

• Ensuring completeness and comprehensibility of documentation and data, e.g. number of cases and variables, variable names, question-variable links;
• Checking variable and value labels;
• Controls for adequate anonymisation of the data;
• Verifying treatment of missing values;
• Checking and enhancing the metadata if necessary;
• Conversion into suitable archival storage and dissemination formats.

FORS also provides guidelines for documenting and preparing quantitative and qualitative data (FORS, n.d.) for deposit.

United Kingdom (UK Data Service)

YES

UK Data Service does quality checks of the deposited data and metadata. For self-deposited research (ReShare repository, UK Data Service, 2017a) we check (UK Data Service, 2017b) for disclosure risk, copyright breaches, the validity of file formats and level of documentation. For curated data (large surveys) we review and process the data (UK Data Service, 2017c).