Abstract

The rise of Big Data and, more in general, of new data sources (social media, satellite images, sensor data, etc.) is rapidly changing official statistics’ context. National Statistical Institutes (NSIs) are obliged to change the way they perform their core business, i.e., the production of relevant, timely and high-quality statistical outputs.
In traditional surveys, domain experts, researchers and IT experts work on tools and methods tailored to the specific statistical domain, therefore it is very difficult, if not impossible, to share code and methods. In order to remain relevant and attractive to young researchers NSIs should perform a ‘mind shift ’both at organizational and technological level. Domain experts, researchers and IT experts should start working closely on methods shared at NSIs or, even better, at international level. Further they should align to modern architecture principles that foster cross-domain interaction, e.g., github for code versioning, microservices to access algorithms through api, continuous integration and continuous delivery (CI/CD) tools to automate code release on production environment, cloud architecture for installation and deployment.

Within this context, a few years ago, Istat launched a set of “Experimental Statistics”, aiming at experimenting the use of new sources and the application of innovative methods in producing data. In this paper we focus on “Cosmopolitics” a new experimental statistic designed and implemented according to the architecture principles highlighted below.