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.
Keywords: big data; camera trap data management; camera trapping; data annotation; data storage; ecological monitoring; metadata; standardization.