GenPopWeb2 is a network of UK-based academic and non-academic partners. These include government departments, survey organisations, academics and major Economic and Social Research Council (ESRC) investments. The network was formed to share knowledge and collaborate in the area of online data collection in social surveys, and to help set the research agenda in this area. The network also shares learning and experiences in relation to the impact of the COVID-19 pandemic for survey research.

GenPopWeb2's main principle is knowledge exchange and it has strong links with NCRM, which has sharing good practice as a core goal. To achieve this, the network organises events that address various issues associated with transitioning to online data collection. The network also produces guidance materials, literature and evidence reviews, all of which are available on our resources page.

The project built on the original GenPopWeb network and on the results of the international conference on the future of online data collection in social surveys. GenPopWeb2 was funded by ESRC and ran from February 2020 to March 2021.


GenPopWeb2 has three main themes. These are:

  1. Sampling and participation, with a particular focus on barriers to transitioning to online data collection for cross-sectional and longitudinal surveys. This theme covers sampling frames and recruitment approaches for push-to-web surveys, response maximisation, as well as hard-to-reach and off-line populations.
  2. Measurement issues, with a particular focus on questionnaire design for mobile devices, including length and modularisation, and complex measurements such as bio-measures, cognitive assessments, as well as data linkage consents.
  3. Adjustment approaches, with a particular focus on accounting and adjusting for measurement differences due to device and mode effects at the analysis stage, including guidance for users, as well as on measurement comparability in the context of time series and longitudinal data.

GenPopWeb2 resources and further information