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      Software to facilitate and streamline camera trap data management: A review

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          Abstract

          Improving technology and increasing affordability mean that camera trapping—the use of remotely triggered cameras to photograph wildlife—is becoming an increasingly common tool in the monitoring and conservation of wild populations. Each camera trap study generates a vast amount of data, which need to be processed and labeled before analysis. Traditionally, processing camera trap data has been performed manually by entering data into a spreadsheet. This is time‐consuming, prone to human error, and data management may be inconsistent between projects, hindering collaboration. Recently, several programs have become available to facilitate and quicken data processing. Here, we review available software and assess their ability to better standardize camera trap data management and facilitate data sharing and collaboration. To identify available software for camera trap data management, we used internet searches and contacted researchers and practitioners working on large camera trap projects, as well as software developers. We tested all available programs against a range of software characteristics in addition to their ability to record a suite of important data variables extracted from images. We identified and reviewed 12 available programs for the management of camera trap data. These ranged from simple software assisting with the extraction of metadata from an image, through to comprehensive programs that facilitate data entry and analysis. Many of the programs tested were developed for use on specific studies and so do not cover all possible software or data collection requirements that different projects may have. We highlight the importance of a standardized software solution for camera trap data management. This approach would allow all possible data to be collected, enabling researchers to share data and contribute to other studies, as well as facilitating multi‐project comparisons. By standardizing camera trap data collection and management in this way, future studies would be better placed to guide conservation policy on a global level.

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          Most cited references38

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          unmarked: AnRPackage for Fitting Hierarchical Models of Wildlife Occurrence and Abundance

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            REVIEW: Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes

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              Big data and the future of ecology

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                Author and article information

                Contributors
                j.rodemargono@chesterzoo.org
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                06 September 2018
                October 2018
                : 8
                : 19 ( doiID: 10.1002/ece3.2018.8.issue-19 )
                : 9947-9957
                Affiliations
                [ 1 ] School of Life Sciences University of Nottingham Nottingham UK
                [ 2 ] IUCN/SSC Asian Wild Cattle Specialist Group, c/o Chester Zoo Chester UK
                [ 3 ] The North of England Zoological Society/Chester Zoo Chester UK
                [ 4 ] Zoological Society of London London UK
                Author notes
                [*] [* ] Correspondence

                Johanna Rode‐Margono, Chester Zoo, Upton‐by‐Chester, England, UK.

                Email: j.rodemargono@ 123456chesterzoo.org

                Author information
                http://orcid.org/0000-0001-6984-8323
                Article
                ECE34464
                10.1002/ece3.4464
                6202726
                30386588
                2a112e2a-ad7b-40db-bd56-c0a8010595aa
                © 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 30 January 2018
                : 28 May 2018
                : 18 June 2018
                Page count
                Figures: 0, Tables: 1, Pages: 11, Words: 8716
                Categories
                Review
                Reviews
                Custom metadata
                2.0
                ece34464
                October 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.5.1 mode:remove_FC converted:26.10.2018

                Evolutionary Biology
                big data,camera trap data management,camera trapping,data annotation,data storage,ecological monitoring,metadata,standardization

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