European Working Conditions Survey 2024: Data validation and editing report

Data editing and validation are a very important part of the data collection and review process to ensure data accuracy, consistency, comparability and reliability. 

They detect interviewer errors, correct inconsistencies, and validate skip patterns and employmentrelated logic (e.g. job status, hours, income). Cleaning harmonises data across countries, languages and fieldwork agencies, ensuring standard classifications (occupation, sector of activity, education, region) are applied correctly. It identifies outliers, checks demographic plausibility, prepares variables for weighting, and removes accidental identifiers for data protection compliance. Through systematic validation and documentation, data cleaning protects the integrity of the probability sample and enables meaningful crosscountry labour market analysis. 

Validation occurred before, during and after fieldwork, including script quality assurance, embedded logic and value checks, and real‑time monitoring through a fieldwork monitoring tool. A significant number of checks were built into the questionnaire, covering routing errors, inconsistent replies, implausible values and outliers. Most respondents triggered very few flags, with 98% of face‑to‑face and 94% of online interviews generating fewer than four warnings—evidence of robust overall data quality.  

Compliance with sampling and contact protocols was also assessed. A relatively small number of interviewers were flagged for review, with some interviews being deleted due to back‑check failures, protocol breaches, insufficient coding, or post‑fieldwork quality indicators.  

Additional issues included routing inconsistencies, timestamp irregularities and the need to revise data‑processing pipelines.  

Annexes