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.

The Italian way to an online probability panel / Taddei, Luciana; Biolcati Rinaldi, Ferruccio; Heins, Frank; Marchesini, Nicolo'; Paparusso, Angela; Pennacchiotti, Claudia; Piacentini, Francesco; Primerano, Ilaria; Vezzoni, Cristiano; Santurro, Michele. - (2026), pp. 141-152. [10.1007/978-3-032-07005-0_11].

The Italian way to an online probability panel

Taddei, Luciana;Biolcati Rinaldi, Ferruccio;Marchesini, Nicolo';Paparusso, Angela;Pennacchiotti, Claudia;Vezzoni, Cristiano;Santurro, Michele
2026

Abstract

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.
2026
Longitudinal data infrastructures in Europe. Tools for open science in social science research
9783032070043
9783032070050
panel data; IOPP; ppen data; FAIR data; online probability panel
02 Pubblicazione su volume::02a Capitolo o Articolo
The Italian way to an online probability panel / Taddei, Luciana; Biolcati Rinaldi, Ferruccio; Heins, Frank; Marchesini, Nicolo'; Paparusso, Angela; Pennacchiotti, Claudia; Piacentini, Francesco; Primerano, Ilaria; Vezzoni, Cristiano; Santurro, Michele. - (2026), pp. 141-152. [10.1007/978-3-032-07005-0_11].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1757125
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