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In this discussion paper, we outline the motivations and the main principles of the Trusted Smart Statistics (TSS) concept that is under development in the European Statistical System. TSS represents the evolution of official statistics in response to the challenges posed by the new datafied society. Taking stock from the availability of new digital data sources, new technologies, and new behaviors, statistical offices are called nowadays to rethink the way they operate in order to reassert their role in modern democratic society. The issue at stake is considerably broader and deeper than merely adapting existing processes to embrace so-called Big Data. In several aspects, such evolution entails a fundamental paradigm shift with respect to the legacy model of official statistics production based on traditional data sources, for example, in the relation between data and computation, between data collection and analysis, between methodological development and statistical production, and of course in the roles of the various stakeholders and their mutual relationships. Such complex evolution must be guided by a comprehensive system-level view based on clearly spelled design principles. In this paper, we aim at providing a general account of the TSS concept reflecting the current state of the discussion within the European Statistical System.

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.

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Following the increasing penetration of the internet, the number of websites that advertise jobs is growing. The European Centre for the Development of Vocational Training (Cedefop) and the ESSnet Big Data have engaged in parallel projects to assess the feasibility of using online job advertisements (OJA) for labour market analysis and job vacancy statistics. After an initial feasibility study finalised in 2016, Cedefop is developing a Pan-EU system providing information on skills demand present in OJA, which will be operational by 2020. The ESSnet has focussed on statistics that can be derived from OJA and entered into a second phase in November 2018 aiming at creating the conditions for a larger scale implementation of the use of OJA in official statistics. This paper builds on experiences gathered in both projects and identifies opportunities and limitations of using OJA for the above-mentioned purposes. In addition, it discusses the feasibility of creating a joint system for processing and analysing OJA data based on discussions that have taken place in the past two years between Cedefop and the ESSnet Big Data on both projects. In this respect, this paper outlines a possible partnership between Cedefop and the European Statistical System to create and manage a unique source of OJA data that would serve multiple uses in the domain of labour market analysis and official statistics. It presents potential types of (statistical) data and variables based on the information contained in OJAs at European, national and regional levels. Data limitations linked to OJAs nature and specificities will be stressed, too. The paper concludes that there is high potential for combining institutional efforts and creating a joint data collection and processing system on OJA and intends to feed a discussion on the feasibility and the implications of creating a European system for OJA, which can serve European and national needs.