Presentation short abstract

The study examines how digital citizen science initiatives structure composition, control, access, and use of data in Tanzania’s forested landscapes. It reveals underlying power dynamics in digital monitoring and identifies opportunities for just and inclusive data practices for forest monitoring.

Presentation long abstract

Digital citizen-science initiatives are hyped to decolonise forest monitoring, as they facilitate local people’s participation in tool designing, data interpretation and decision-making. However, these processes often embed predefined assumptions about what data is worth collecting, how it should be collected, and which indicators are prioritised, raising concerns about the neutrality and inclusiveness. There remains a limited understanding regarding how power and politics shape data acquisition, storage and management. Informed by Pritchard et al. (2022)'s data justice framework and grounded in selected digital citizen science initiatives in Tanzania, this study examines how these initiatives shape the composition, control, access, processing, and use of digitally monitored forest data. I reviewed the initiatives’ documents, conducted interviews and focus group discussions, and acted as participant observer to explore these data justice elements. Firstly, data composition: unpacking what is visible or hidden in terms of forest management, landscapes’ species and whose ways of knowing are considered. Secondly, data control: examining who sets rules by highlighting the roles of implementing NGOs and local communities, who design data protocols and decide on data sharing procedures. Thirdly, data access: assessing channels through which data flows, accessibility to the public, and who can retrieve data and benefit. And fourthly, data processing and use: interrogating epistemic assumptions that guide how raw data are aggregated, filtered, and visualised. Generally, the study envisions pathways for just and plural processes in the designing, governance, and interpretation of digitally monitored forest data, to enable the embedding of decolonial possibilities into digital citizen science initiatives.