The impact of human activities on the physical environment are largely responsible for the observed loss of habitats, high levels of extinction, irreversible threats to biodiversity and loss of livelihoods. Ecosystem monitoring programmes, corrective measures and rehabilitation initiatives to combat these ecological threats are largely driven by, and dependent on data.

These initiatives are informed by ecological data covering large spatial and temporal scales. Recent reviews on ecological data needs acknowledge that ecology has joined the world of ‘big data’. 1] Catching up with increasing ecological data needs requires a shift from the traditional or expert-sourced data approaches to acquiring supplementary data from communities living in close proximity to target ecosystems.

This has given rise to citizen science, which is becoming increasingly recognised. Citizen science involves the participation of non-professional or amateur community scientists in scientific inquiries and monitoring programmes, often on a voluntary basis.[2] Citizen science, though relatively new, has demonstrated that it can generate high-quality data to supplement national data sets.[3]^;[4]

However, some scientists question the quality of the data generated by citizen scientists. Some have identified flaws in crowd-sourced data, including deviations from standard protocols and biases in recording or in the choice of sampling sites.[5] Where flaws in citizen science data have been identified, the question remains: Are the tools appropriately designed to suit their use or execution by non-professionals? Experts have identified institutional barriers, insufficient access to suitable technology and inaccessible language as the leading impediments for most citizen science initiatives.[6]

Language, in particular, constitutes an important barrier to effective participation in ecological citizen science initiatives.[7] South Africa has access to an important biological monitoring citizen science tool called the miniSASS tool.[8] MiniSASS utilises sampled macroinvertebrates to determine the state of a river’s health. Yet the miniSASS is a prime example of how language can be a barrier preventing citizen scientists’ full participation in biomonitoring. An audit of the miniSASS undertaken by Graham in 2012 emphasised that it was necessary to translate the tool from English into other South African languages.[9] This is an essential undertaking and will assist in ensuring that monitoring tools are adequately modified to suit the linguistic aptitudes and entry competences of South African citizen scientists.

However, translating the tool from English or scientific terminologies to target South African languages in itself holds significant challenges. Unlike its scientific counterparts, folk nomenclature is largely undocumented and, where it is documented, studies have shown that folk nomenclature and taxonomy vary from one region to another and among speakers of the same language.[10]^;[11] Some terminologies will therefore have no corresponding translations in some of the South African languages (an observation indicative of a lack of isomorphic correspondence between the source text and target languages).

Dr Nhlanhla Mnisi is a postdoctoral fellow in the Department of African Languages, Faculty of Humanities at the University of Pretoria. He is also a Senior Atlantic Fellow for Racial Equity (hosted by the Nelson Mandela Foundation and Columbia University). Mnisi obtained his PhD in Aquatic Sciences (Freshwater Ecology) from the University of the Witwatersrand in 2018.