Citizen scientists collecting data using apps in Nakuru, Kenya

Citizen scientists collecting data using apps in Nakuru, Kenya. Photo: William Apondo / SEI.

Progress towards the SDGs is monitored using a set of targets and indicators. Gaps in official datasets have led to calls for the inclusion of data generated through citizen science (CS) and allied approaches. Co-benefits of CS mean these approaches could also contribute to localising, defining, and achieving the SDGs. However, mapping of current and potential contributions is needed, as well as an understanding of the challenges these approaches present.

This paper reports on a semi-systematic review of past and current CS projects and their assessment against different dimensions of CS: spatial, temporal, thematic, process, and management, as well as their value for the SDGs set out by Fritz et al. in 2019 , focusing on LMIC cities as key environments in the battle for sustainability.

Interviews were conducted with project leaders to further understand the challenges for CS in these contexts. Opportunities are found for projects to monitor and achieve a wide range of goals, targets, and indicators. However, the authors identified fewer projects in low income countries when compared with middle income countries. Challenges for LMICs include balancing local needs with national monitoring requirements and lack of long-term funding.

In conclusion, the paper suggests greater support is needed for LMICs to fully achieve the potential of CS to monitor SDGs.