The features and processes underpinning high-quality data generation in participatory research and engagement activities

Participatory approaches are widely used by researchers to gather data and insight about how the environment is perceived, valued and used. The participatory activities may be creating information as part of curiosity-driven blue-skies research or to inform policy/practise decision-making. The quality and usability of data derived from participatory approaches are heavily influenced by how activities are conducted. We share a set of features and processes that underpin the generation of high-quality data, based on our collective experience of developing and undertaking participatory activities with an environmental and conservation focus. We propose four general features: (a) Depth and breadth of engagement; (b) robustness of the approach; (c) allowing space for surprises; (d) usability across contexts. We also provide a practical toolbox of processes, and associated facilitation techniques, which can be employed to maximise participant engagement and generate quality data. The features and processes are a practical guide for project leaders/teams to consider in the context of their work, rather than a set of inflexible rules. They should be relevant regardless of the participatory methods used, or the research, policy or practice setting being addressed.

Automated summary

This article outlines how participatory approaches can generate high-quality data by focusing on aspects such as depth and breadth of engagement, robustness of the approach, allowing for surprises, and usability across different contexts. It also provides a practical toolbox of processes and facilitation techniques to maximize participant engagement and data quality. These features and processes serve as a practical guide for project leaders/teams to consider in their work, regardless of the participatory methods used or the specific setting being addressed.