Citizen Data and Official Statistics: Background Document to a Collaborative Workshop

Grommé, Francisca; Ustek, Funda; Ruppert, Evelyn and Cakici, Baki. 2017. Citizen Data and Official Statistics: Background Document to a Collaborative Workshop. ARITHMUS Working Paper Series, London. [Other]

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Abstract or Description

This working paper was written in preparation for a collaborative workshop organised for statisticians, social scientists, information and app designers and other participants inside and outside academia. The autumn 2017 workshop aimed to develop the main principles for a citizen data app for official statistics. Through this work we sought to conceive of a new regime of data collection in official statistics through different devices. How can we capture citizens’ meanings and intentions when they produce data? Can we develop ‘smart’ methods that do not rely on cooperating with, and data generated by, large tech companies, but by developing methods and data co-produced with citizens? Towards addressing these issues we developed four key concepts outlined in this document: experimentalism, citizen data, smart statistics and privacy by design. We introduced these concepts to facilitate shared understandings of their meaning, provide a background to discussions about them and the questions they raise for official statistics. Through then jointly working on the practical development of a citizen data app, the objective was to reflect on and reshape these concepts and to identify other concepts that might aid our understanding of the possibilities of citizen co-production of data for official statistics.

Item Type:

Other

Identification Number (DOI):

https://doi.org/10.13140/RG.2.2.18532.88966

Keywords:

smart statistics, practice-based research, Big Data, citizen science, experimentalism, privacy by design

Departments, Centres and Research Units:

Sociology > Centre for Invention and Social Process (CISP) [2016-]

Date:

6 July 2017

Item ID:

20740

Date Deposited:

13 Jul 2017 09:04

Last Modified:

29 Apr 2020 16:28

URI:

https://research.gold.ac.uk/id/eprint/20740

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