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Automated synthesis of biodiversity knowledge requires better tools and standardised research output

Cornford, Richard; Millard, Joseph; Gonzalez-Suarez, Manuela; Freeman, Robin; Johnson, Thomas Frederick; (2022) Automated synthesis of biodiversity knowledge requires better tools and standardised research output. Ecography , 2022 (3) , Article e06068. 10.1111/ecog.06068. Green open access

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Abstract

As the impact of anthropogenic activity on the environment has grown, research into biodiversity change and associated threats has also accelerated. Synthesising this vast literature is important for understanding the drivers of biodiversity change and identifying those actions that will mitigate further ecological losses. However, keeping pace with an ever-increasing publication rate presents a substantial challenge to efficient syntheses, an issue which could be partly addressed by increasing levels of automation in the synthesis pipeline. Here, we evaluate the potential for automated tools to extract ecologically important information from the abstracts of articles compiled in the Living Planet Database. Specifically, we focused on extracting key information on taxonomy (studied species names), geographic location and estimated population trend, assessing the accuracy of automated versus manual information extraction, the potential for automated tools to introduce biases into syntheses, and evaluating if synthesising abstracts was enough to capture the key information from the full article. Taxonomic and geographic extraction tools performed reasonably well, although information on studied species was sometimes limited in the abstract (compared to the main text) preventing fast extraction. In contrast, extraction of trends was less successful, highlighting the challenges involved in automating information extraction from abstracts, such as deficiencies in the algorithms, linguistic complexity associated with ecological findings, and limited information when compared to the main text. In light of these results, we cautiously advocate for a wider use of automated taxonomic and geographic parsing tools for ecological synthesis. Additionally, to further the use of automated synthesis within ecology, we recommend a dual approach: development of improved computational tools to reduce biases; and enhanced protocols for abstracts (and associated metadata) to ensure key information is included in a format that facilitates machine-readability.

Type: Article
Title: Automated synthesis of biodiversity knowledge requires better tools and standardised research output
Open access status: An open access version is available from UCL Discovery
DOI: 10.1111/ecog.06068
Publisher version: https://doi.org/10.1111/ecog.06068
Language: English
Additional information: © 2022 The Authors. Ecography published by John Wiley & Sons Ltd on behalf of Nordic Society Oikos This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Keywords: Science & Technology, Life Sciences & Biomedicine, Biodiversity Conservation, Ecology, Biodiversity & Conservation, Environmental Sciences & Ecology, data extraction, ecology, literature synthesis, machine learning, population trends, text mining
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
URI: https://discovery.ucl.ac.uk/id/eprint/10146171
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