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Do big unstructured biodiversity data mean more knowledge?

Bayraktarov, E; Ehmke, G; O'Connor, J; Burns, EL; Nguyen, HA; McRae, L; Possingham, HP; (2019) Do big unstructured biodiversity data mean more knowledge? Frontiers in Ecology and the Environment , 6 , Article 239. 10.3389/fevo.2018.00239. Green open access

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Abstract

Conserving species biodiversity demands decisive and effective action. Effective action requires an understanding of species population dynamics. Therefore, robust measures which track temporal changes in species populations are needed. This need, however, must be balanced against the scale at which population change is being assessed. Advances in citizen science and remote sensing technology have heralded an era of “big unstructured data” for biodiversity conservation. However, the value of big unstructured data for assessing changes in species populations, and effectively guiding conservation management has not been rigorously assessed. This can be achieved only by benchmarking big unstructured data against high-quality structured datasets, and ensuring the latter are not lost through an over-emphasis on “big data.” Here, we illustrate the current trend to disproportionately prioritize data quantity over data quality and highlight the discrepancy in global availability between both data types. We propose a research agenda to test whether this trend will result in a net decrease of useful knowledge for biodiversity conservation. We exemplify this by examining the availability of big unstructured data vs. standardized data using data from global repositories on birds as an example. We share experiences from the data collation exercise needed to develop the Australian Threatened Species Index. We argue there is an urgent need to validate and enhance the utility of big unstructured data by: (1) maintaining existing well-designed, standardized long-term species population studies; (2) strengthening data quality control, management, and curation of any type of dataset; and (3) developing purpose-specific rankings to assess data quality.

Type: Article
Title: Do big unstructured biodiversity data mean more knowledge?
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fevo.2018.00239
Publisher version: https://doi.org/10.3389/fevo.2018.00239
Language: English
Additional information: © 2019 Bayraktarov, Ehmke, O'Connor, Burns, Nguyen, McRae, Possingham and Lindenmayer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: environmental policies, sound decision-making, species monitoring, species population trends, structured long-term monitoring data, threatened species, value of big data for conservation
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
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
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment
URI: https://discovery.ucl.ac.uk/id/eprint/10066761
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