BLOG: Adaptable activities for engaging the public with data research
Categories: Blogs, Public engagement
14 September 2026
Conversations can quickly become technical, making it harder for people to understand how data research relates to their lives. At Research Data Scotland (RDS) and ADR Scotland, we have found that one of the most effective ways to begin these conversations is through interactive public engagement activities that can be adapted to the audience and the research being shared. Over the last few years, we've developed a range of flexible public engagement activities designed to help people explore how data is used for research and become confident that all data is stored safely.
Rather than being designed around a single project, they can be adapted to different research topics, age groups, and settings. Each one aims to make complex ideas more accessible while creating opportunities for discussion.
Making the abstract tangible
One of our most popular activities invites participants to become data researchers themselves. In our LEGO® activity, participants apply for access to LEGO 'data', choose a researcher name, select datasets, and promise to keep that data safe. We then 'accept' the form before the participants use the LEGO to create something based on the information they have selected.
The activity introduces concepts such as accessing data, using secure environments, and linking data to answer research questions. The datasets can also be changed depending on the topic being discussed. This allows the activity to be used by other researchers and organisations to explain similar ideas.
The same principle underpins many of our other activities. Our maze activity challenges children to identify the correct datasets to answer a research question, demonstrating how data can be linked together to generate new insights. Meanwhile, our card matching activity encourages older audiences to sort and connect datasets using anonymous identifiers, introducing the concept of data linkage and pseudonymisation in an accessible way. In both cases, the datasets and scenarios can be adapted whilst demonstrating the same underlying principles.