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.

Probabilistic panel infrastructures are becoming essential components of Europe’s social science research ecosystem. Their methodological rigour, capacity for longitudinal tracking, and alignment with FAIR (Findable, Accessible, Interoperable, Reusable) principles make them particularly well-suited to addressing the complexity of contemporary societal dynamics. Italy, in alignment with broader European trends, is adopting and developing such infrastructures by integrating advanced statistical tools, digital innovation, and open science practices. This chapter discusses the role of the European Commission, the European Strategy Forum on Research Infrastructures—ESFRI Roadmap, the European Research Infrastructure Consortium (ERIC) legal framework and the European Open Science Cloud (EOSC) environment, underlining how social science in Italy is aligning and evolving to achieve the standards indicated by mayor longitudinal social science research infrastructures. This chapter serves as an introduction to key European social research infrastructures that are further explored in the following chapters. It briefly presents the Survey of Health, Ageing and Retirement in Europe (SHARE-ERIC) and the Consortium of European Social Science Data Archives (CESSDA-ERIC) as foundational tools for Open Science in the social sciences and outlines the implementation of international surveys such as Survey of Health, Ageing and Retirement in Europe (SHARE), Generations and Gender Survey (GGS) and Growing Up in Digital Europe (GUIDE) in Europe and in its implementation in Italy. The chapter also introduces the first Italian Online Probability Panel (IOPP), currently under development, as a solution to avoid effort duplication and provide fast and dependable data for researchers.

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.

Secondary data represent a vital components in the toolkit of social scientists. Among them, panel and longitudinal data are especially valuable for observing changes within a sample population over time. This chapter aims to highlight the power of these data sources by which social scientists can uncover valuable insights that inform policy decisions, shape interventions, and contribute to our understanding of the world. To be more effective and useful for the purposes of use by public institutions or academies and research institutions in the extemporaneous reading of social phenomena, the characteristic of the speed with which the phenomena studied are detected and analyzed constitutes a significant added value which makes Research Infrastructures on longitudinal and panel data in social science, unique in its kind, and is inserted into a lack of information that is crucial.

This chapter examines the integration of digital traces into welfare research from a methodological and epistemological perspective grounded in survey methodology. It argues that, although digitally generated data are analytically rich, they are insufficient for producing high-quality welfare evidence when detached from explicit research designs, as they lack defined reference populations, observable selection mechanisms, and contextual information. The chapter proposes Online Probability Panels as a methodological solution, conceptualised as research infrastructures that anchor digital traces within probability-based sampling and longitudinal designs. By linking digital data to inclusion probabilities, socio-demographic characteristics, and repeated observations, these infrastructures enable population inference, assessment of selection bias, and modelling of uncertainty. The chapter shows that high-quality data science for welfare governance depends on integrating digital traces within infrastructures that ensure interpretability, transparency, and methodological robustness.