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Output Checking in Research Data Centres - 2024

Output Checking in Research Data Centres 
Course LeadersAnnu Cabrera
Target GroupThe course is intended for staff checking output that was created by external researchers or output from varying statistical analyses created by colleagues in statistical offices.
Entry Qualifications
  • Sound command of English. Participants should be able to make short interventions and to actively participate in discussions
  • The objective of this course is to introduce participants to the practice of output checking for confidentiality risks. The course focuses on output that is generated by researchers from official microdata. In most cases researchers will have had access to microdata through the Research Data Centre of the data producer to produce the output. The participants will be invited to bring their own case studies for discussion in the training.
  • Review of statistical disclosure control methodology;
  • Approaches for checking tabular output and non-tabular output;
  • Researcher training;
  • Practical case studies from MS;
  • Software example
Expected OutcomeBetter understanding of theory and methods used when statistical output that has been created by researchers is checked for statistical confidentiality.
Training Methods
  • The course programme is a mix of theory and practice with an emphasis on the practical use of the tools. The following training methods will be used:
  • Presentations and lectures
  • Demonstration of the recommended software tools
  • Hands-on software session allowing participants going through the whole census protection process
  • Exchange of views/experiences on national practices
Required ReadingNone
Suggested Reading

Guidelines for Output Checking  

Statistical Disclosure Control (2012) by A. Hundepool, J. Domingo-Ferrer, L. Franconi, S. Giessing, E. Schulte Nordholt, K. Spicer and P.P. de Wolf, Wiley Series in Survey Methodology, ISBN 978-1-1199-7815-2

Required PreparationParticipants will be required to bring and present two examples of output for discussion in the training. These should be two outputs that they themselves or colleagues have checked in their Statistical Institute and found challenging or interesting or that illustrate a rule of output checking.


Annu Cabrera (Statistics Finland)

Eric Schulte Nordholt (Statistics Netherlands)

Peter-Paul de Wolf (Statistics Netherlands)



Practical Information    
WhenDurationWhereOrganiserAPPLICATION VIA National Contact Point
09–10.10.20242 daysHelsinki, Finland


Public Sector GmbH

Deadline: 12.08.2024