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The 2013 Seminar on statistical data collection was held in Geneva, Switzerland, from 25 - 27 September 2013. 

The second Seminar on Statistical Data Collection was held in Geneva, Switzerland, from 25-27 September 2013. It was attended in person by participants from Australia, Azerbaijan, Canada, Denmark, Estonia, Finland, France, Georgia, Germany, Hungary, Ireland, Israel, Italy, Mongolia, the Netherlands, Poland, Portugal, Republic of Korea, the Russian Federation, Singapore, Slovenia, Sweden, Turkey and the United Kingdom of Great Britain and Northern Ireland. The Statistical Office of the European Union (Eurostat), the International Labour Organization, the International Monetary Fund, the Organisation for Economic Cooperation and Development and the World Intellectual Property Organization were also represented. Representatives of New Zealand and the United States of America participated remotely via video link.

The seminar considered the following substantive topics:

  • (i) Centralising data collection;
  • (ii) Managing data collection functions in a changing environment;
  • (iii) Improving the respondent experience;
  • (iv) Multiple modes of data collection;
  • (v) Integration and management of new data sources.

Ideas proposed for future work activities to be led by UNECE included:

  • Continue to hold seminars on data collection on an annual or biennial basis
  • Combine data collection and dissemination/communication seminars to permit some joint elements
  • Provide a platform for sharing materials (case studies, strategy documents, research results, collection tools) amongst the data collection community via electronic repositories and/or a ‘lessons learned database’
  • Collate examples of how GSIM has been or could be used to improve the data collection process.

Topics proposed for the focus of future activities included, amongst others:

  • More examples of transitioning to centralized systems, especially of fast transitioning; advantages & disadvantages
  • Experiences from other countries and best practices in mixed mode or web data collection (experiments, parallelisms, survey designs)
  • Measuring cost savings from mode changes
  • Architecture for data collection
  • Management systems for all modes.

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