The Italian Online Probability Panel (IOPP) is the first initiative in Italy designed to produce high-quality longitudinal survey data for monitoring social transformations. Developed in alignment with leading European experiences—such as LISS, ELIPSS, GESIS panel, etc.—it brings Italy into the broader landscape of advanced survey infrastructures, enabling both cross-sectional and longitudinal analyses. Launched in early 2025, IOPP is based on an offline recruitment strategy using a push-to-web approach, drawing from a nationally representative probability sample of approximately 10,000 individuals aged 18–74 from the national population register. The data collection is structured around five annual CAWI waves, centred on a core questionnaire that tracks stable constructs such as family and housing, health, education, employment, income, leisure, social integration, and political attitudes. These are complemented by rotating or one-time modules developed through open calls to the research community. To ensure inclusivity, the panel also integrates offline participants through paper questionnaires sent via postal mail. The calibration phase is expected to conclude by the end of 2025, with the panel fully operational from 2026. Data will be released in compliance with FAIR and Open Science principles with the aim of offering a collaborative infrastructure, which encourages contributions from a wide range of stakeholders, including researchers, policymakers, and public institutions.

This chapter examines how probabilistic and longitudinal surveys provide robust, policy-relevant evidence for understanding social, demographic, and economic change. It presents the Italian Life Course Observatory as a strategic infrastructure that integrates four complementary data sources (GUIDE, GGS, SHARE, and IOPP), enabling continuous and comparable monitoring across all stages of life. The chapter highlights the value of probability-based designs for producing reliable indicators, as well as the main operational and methodological challenges—such as response decline, coverage gaps, attrition, and panel conditioning—that can affect policy analyses if not properly addressed. It also shows how the adoption of FAIR principles and interoperable digital infrastructures strengthens data accessibility, transparency, and reusability for public institutions. Overall, the chapter demonstrates how integrated, high-quality longitudinal evidence can support more timely, targeted, and effective policymaking in areas such as education, labour markets, family dynamics, ageing, and social welfare.

Online Probability Panels (OPPs) have emerged as essential research infrastructures for social sciences, offering robust tools for longitudinal analysis and evidence-based policy-making. However, the growing role of the Open Science movement demands systematic evaluation of their compliance. This study compares major European OPPs—including LISS, GESIS, the GIP, ELIPSS, and the Swedish and Norwegian Citizen Panels—focusing on their practices of openness, recruitment, sampling, and maintenance. Through a qualitative analysis of public documentation and methodological reports, the study examines how their diverse approaches influence data accessibility, inclusivity, and long-term usability. Our findings highlight substantial variability across panels, reflecting the interplay between national contexts, governance models, technological infrastructures, and methodological choices related to recruitment, sampling, and panel maintenance. Some panels demonstrate stronger alignment with Open Science values—promoting transparency, interoperability, and inclusive engagement—while others operate within more constrained frameworks shaped by institutional or structural limitations. This comparative analysis contributes to the understanding of OPPs as evolving knowledge infrastructures and provides a reference framework for future panel development. In doing so, it offers valuable insights for enhancing the role of OPPs in advancing open and socially engaged research practices.

This chapter analyzes the strategic role of training within Research Infrastructures (RIs) in the Social Sciences, with particular reference to the experience developed within the FOSSR project. Drawing on the framework of European and international policies on Open Science, the paper argues that capacity-building activities are not an ancillary service of RIs, but rather an essential condition for their scientific effectiveness, sustainability, and transformative capacity. The FOSSR training strategy was structured as a multilevel model encompassing online learning, participatory constructivist sessions, and advanced higher education programmes, such as postgraduate courses and doctoral scholarships. The chapter illustrates the design, implementation methods, and some participation indicators, highlighting high levels of satisfaction and inclusiveness, with particular attention to the territorial dimension and gender balance. The FOSSR experience demonstrates a commitment to effectively make RIs open, collaborative, and reflective ecosystems. By combining awareness-raising, the skilled use of shared data and services, and transformative learning practices, the FOSSR approach promotes the advancement of a model of knowledge production based on shared innovative tools and data. Furthermore, it fosters participation beyond academia, engaging researchers, policymakers, and civil society actors in the pursuit of a more open and inclusive science.