Speeding Up Evidence Synthesis for Conservation

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Client: Phil Martin, Department of Zoology <pam79@cam.ac.uk>

A core activity of the Conservation Evidence team in the Department of Zoology is compiling and summarising research literature, to provide evidence for which management approaches are most effective for biodiversity conservation. However, this evidence is dispersed in many different scientific journals, in English and non-English language journals, and in non-academic (“grey”) literature. The Group needs tools that can use natural language processing methods to constantly monitor publications across many different venues, initially classifying studies as relevant or not to different biological taxa, and then extracting key attributes such as geography, habitat, threats or interventions and organising these for thematic browsing or targeted queries. The group would also like to explore the possibility of using natural language processing to summarise study findings.