Trusted Smart Surveys: Architectural and Methodological Challenges Related to New Data Sources

Abstract

In the last few years, Official Statistics have been deeply impacted by the development of smart technologies. This paper summarizes the architectural achievements and the main methodological aspects of the ESSnet (European Statistical System network project) on Smart Surveys, launched at the beginning of 2020. The main goal of the ESSnet is to deliver preparatory work for the development of a European platform, to share und re-use methods and tools for smart data processing. More precisely, the project aims at implementing and testing a common framework for (trusted) smart surveys, through the design of a reference architecture and the development of methodological and technical capabilities within the European Statistical System (ESS). Further, the use of innovative data sources forces National Statistical Institutes (NSIs) to face new challenges, e.g., access to data owned by public and private parties, data processing across multiple NSIs. Privacy preserving technologies are exploited in this paper with the aim to understand their impact on both the architectural framework and technical requirements of the platform. The expected benefits of developing a shared infrastructure are the decrease of respondent burden, the modernization of statistical processes, as well as the harmonization and enrichment of the statistical output.