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Big Data as a Source for Official Statistics

Piet J.H. Daas
  • Corresponding author
  • Statistics Netherlands, Division of Process development, IT and methodology P.O. Box 4481, 6401 CZ, Heerlen, The Netherlands.
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/ Marco J. Puts
  • Statistics Netherlands, Division of Process development, IT and methodology P.O. Box 4481, 6401 CZ, Heerlen, The Netherlands
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  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Bart Buelens
  • Statistics Netherlands, Division of Process development, IT and methodology P.O. Box 4481, 6401 CZ, Heerlen, The Netherlands.
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  • De Gruyter OnlineGoogle Scholar
/ Paul A.M. van den Hurk
  • Statistics Netherlands, Division of Process development, IT and methodology P.O. Box 4481, 6401 CZ, Heerlen, The Netherlands.
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Published Online: 2015-06-27 | DOI: https://doi.org/10.1515/jos-2015-0016


More and more data are being produced by an increasing number of electronic devices physically surrounding us and on the internet. The large amount of data and the high frequency at which they are produced have resulted in the introduction of the term ‘Big Data’. Because these data reflect many different aspects of our daily lives and because of their abundance and availability, Big Data sources are very interesting from an official statistics point of view. This article discusses the exploration of both opportunities and challenges for official statistics associated with the application of Big Data. Experiences gained with analyses of large amounts of Dutch traffic loop detection records and Dutch social media messages are described to illustrate the topics characteristic of the statistical analysis and use of Big Data.

Keywords: Large data sets; traffic data; social media


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About the article

Received: 2013-08-01

Revised: 2013-08-01

Accepted: 2014-09-01

Published Online: 2015-06-27

Published in Print: 2015-06-01

Citation Information: Journal of Official Statistics, Volume 31, Issue 2, Pages 249–262, ISSN (Online) 2001-7367, DOI: https://doi.org/10.1515/jos-2015-0016.

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© by Piet J.H. Daas. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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