Abstract
This chapter outlines challenges and modern approaches in statistical disclosure control of official high-resolution population data on the example of the EU census rounds 2011 and 2021, where a particular focus is on the European 1 km grid outputs derived from these censuses. After a general introduction to the topic and experiences from 2011, the recommended protection methods for geospatial data in the planned 2021 census 1 km grids are discussed in detail.
The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission.
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Notes
- 1.
Regulation (EC) No 763/2008 of the European Parliament and of the Council of 9 July 2008 on population and housing censuses (OJ L 218, 13.8.2008, p. 14) and its implementing Acts.
- 2.
“Local Administrative Units level 2”, typically representing municipalities.
- 3.
EFGS/GEOSTAT 1 2012. GEOSTAT 1A—Representing Census data in a European population grid. Final report. http://ec.europa.eu/eurostat/documents/4311134/4350174/ESSnet-project-GEOSTAT1A-final-report_0.pdf.
- 4.
The ESS is the joint body of Eurostat and the NSIs of all EU countries and Iceland, Liechtenstein, Norway and Switzerland. It is responsible for the development and quality assurance of official European statistics.
- 5.
For a more detailed discussion on the appropriate/intended framework for the ESS, see Haldorson and Moström (2018), Chap. 9 in this volume.
- 6.
Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on European statistics (OJ L 087 31.3.2009, p. 164), amended by Regulation (EU) 2015/759 of the European Parliament and of the Council of 29 April 2015 (OJ L 123, 19.5.2015, p. 90).
- 7.
…or households etc.; for brevity we simply refer to “persons” in the following.
- 8.
- 9.
This classification of variables is not rigorous because it depends on the prior knowledge of an intruder, where reasonable assumptions need to be made for a risk assessment. Moreover, some variable categories might be considered identifying and sensitive (think about place of birth). Finally, different countries have different perceptions of what is sensitive information—the examples chosen here try to convey an intuitive, common-sense notion of the conceptual difference between identification and disclosure of sensitive information.
- 10.
- 11.
GEOSTAT is a joint cooperation of Eurostat with the European Forum for Geography and Statistics (EFGS); see http://www.efgs.info/geostat/.
- 12.
Directive 2007/2/EC of the European Parliament and of the Council establishing an Infrastructure for Spatial Information in the European Community (INSPIRE) (OJ L 108, 25.4.2007, p. 1) and its implementing Acts.
- 13.
For a comprehensive quality assessment, including a detailed documentation of SDC treatments in the various participating countries, see: http://www.efgs.info/wp-content/uploads/geostat/1b/GEOSTAT1B-Appendix17-GEOSTAT-grid-POP-1K-ALL-2011-QA.pdf.
- 14.
Bringing together around 20 NSI representatives of census teams.
- 15.
To be provided only “as far as possible”, i.e. the planned Regulation (see below) would oblige EU countries to justify the non-provision of these data (e.g. non-availability).
- 16.
Common quality principles for European statistics—including accuracy, comparability and completeness mentioned in the text—are established in the revised “European Statistics Code of Practice” adopted by the ESS Committee on 28 September 2011; more details on http://ec.europa.eu/eurostat/web/ess/about-us/quality.
- 17.
- 18.
Only if equal person count is a necessary requirement for pairing similar households, but this is the default in the recommended method variant.
- 19.
Cf. the ‘Confidentiality’ field of the GEOSTAT 1 quality assessment (Footnote 13).
- 20.
Some particular method setups (not recommended by the project for various reasons partly connected to the hypercubes) would also include perturbations of some ‘0’ counts into non-‘0’, i.e. turning originally unpopulated grid squares into populated ones (cf. Sect. 18.5.1).
- 21.
Note that record swapping (cf. Sect. 18.2.2) may further increase the SDC uncertainty on counts of person characteristics. And of course, all this refers only to the SDC uncertainty: naturally there are additional uncertainties (variance and/or bias) stemming from other sources such as data collection and processing.
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Acknowledgements
The author would like to thank Eric Schulte Nordholt, Sarah Gießing, and all other participants of the ESS project “Harmonized Protection of Census Data in the ESS” for many fruitful discussions, and for their kind permission to use the project deliverables as a key reference for this chapter. The author further owes his gratitude to Ekkehard Petri, who provided valuable expert knowledge and explanations about all geo-referencing aspects, in particular about the GEOSTAT project series.
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Bach, F. (2019). Statistical Disclosure Control in Geospatial Data: The 2021 EU Census Example. In: Döllner, J., Jobst, M., Schmitz, P. (eds) Service-Oriented Mapping. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-72434-8_18
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