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Article type: Research Article
Authors: Ricciato, Fabio* | Wirthmann, Albrecht | Giannakouris, Konstantinos | Reis and, Fernando | Skaliotis, Michail
Affiliations: European Commission, Eurostat 5, rue A. Weicker, L-2721 Luxembourg
Correspondence: [*] Corresponding author: Fabio Ricciato, European Commission, Eurostat 5, rue A. Weicker, L-2721 Luxembourg. E-mail: [email protected].
Abstract: In this contribution we outline the concept of Trusted Smart Statistics as the natural evolution of official statistics in the new datafied world. Traditional data sources, namely survey and administrative data, represent nowadays a valuable but small portion of the global data stock, much thereof being held in the private sector. The availability of new data sources is only one aspect of the global change that concerns official statistics. Other aspects, more subtle but not less important, include the changes in perceptions, expectations, behaviours and relations between the stakeholders. The environment around official statistics has changed: statistical offices are not any more data monopolists, but one prominent species among many others in a larger (and complex) ecosystem. What was established in the traditional world of legacy data sources (in terms of regulations, technologies, practices, etc.) is not guaranteed to be sufficient any more with new data sources. Trusted Smart Statistics is not about replacing existing sources and processes, but augmenting them with new ones. Such augmentation however will not be only incremental: the path towards Trusted Smart Statistics is not about tweaking some components of the legacy system but about building an entirely new system that will coexist with the legacy one. In this position paper we outline some key design principles for the new Trusted Smart Statistics system. Taken collectively they picture a system where the smart and trust aspects enable and reinforce each other. A system that is more extrovert towards external stakeholders (citizens, private companies, public authorities) with whom Statistical Offices will be sharing computation, control, code, logs and of course final statistics, without necessarily sharing the raw input data.
Keywords: Officials statistics, trusted smart statistics, big data
DOI: 10.3233/SJI-190584
Journal: Statistical Journal of the IAOS, vol. 35, no. 4, pp. 589-603, 2019
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