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Citizen science has a strong potential to contribute to the democratisation of science worldwide. In addition, such approaches can lead to the creation of “living” datasets that evolve over time, even in regions where few hydrological instruments have been installed. Citizen science approaches, however, do face a number of hurdles. One major challenge is the need for a central server to receive, manage and host the data contributed by volunteers; such servers require expert knowledge to configure and are also quite costly to maintain or rent over extended periods of time. These difficulties pose a challenge to the long-term financial sustainability of citizen science initiatives in the long term, especially after project funding has ceased. In addition, the centralisation of data on a server creates a very strong dependency for the participating communities; if their access to the internet is limited or costly, or if the server is not maintained after the end of the project, communities will be unable to contribute new data or even view and use previously contributed data. In this context, distributed databases, such as Constellation, offer a different approach. In these systems, every device (phone or computer) that contributes data to or reads data from the network is a client and sever in its own right and can store and transmit community data to other participants in the network, all without the need for a central server. The low barrier to entry and absence of server costs allows such networks to be rapidly developed and deployed with minimal budgets, all while becoming stronger and more resilient as they grow in popularity and users. In the African context, such an approach may contribute to wider adoption of citizen science tools and projects, as well as to better data sovereignty and sustainability. |
