Recent years have seen dramatic changes in sources of data, amounts of data, availability of data, frequency of data, and types of data. Along with advances in data analytic technology these changes have opened up huge possibilities for improving the information content and timeliness of official statistics. in this paper we characterise such 'smart statistics', examining their potential benefits and the obstacles that must be overcome if they are to be trusted and relied upon. In particular, we list eight specific recommendations which we believe producers of smart statistics should adhere to if the full potential for economic and social benefit is to be achieved.

Trusted smart statistics: The challenge of extracting usable aggregate information from new data sources / Vichi, M.; Hand, D. J.. - In: STATISTICAL JOURNAL OF THE IAOS. - ISSN 1874-7655. - 35:4(2019), pp. 605-613. [10.3233/SJI-190526]

Trusted smart statistics: The challenge of extracting usable aggregate information from new data sources

Vichi M.
;
2019

Abstract

Recent years have seen dramatic changes in sources of data, amounts of data, availability of data, frequency of data, and types of data. Along with advances in data analytic technology these changes have opened up huge possibilities for improving the information content and timeliness of official statistics. in this paper we characterise such 'smart statistics', examining their potential benefits and the obstacles that must be overcome if they are to be trusted and relied upon. In particular, we list eight specific recommendations which we believe producers of smart statistics should adhere to if the full potential for economic and social benefit is to be achieved.
2019
Computer-mediated-communication; data sources; data types; indicators; internet of things; machine learning; timeliness; trustworthiness
01 Pubblicazione su rivista::01a Articolo in rivista
Trusted smart statistics: The challenge of extracting usable aggregate information from new data sources / Vichi, M.; Hand, D. J.. - In: STATISTICAL JOURNAL OF THE IAOS. - ISSN 1874-7655. - 35:4(2019), pp. 605-613. [10.3233/SJI-190526]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1364860
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