ArticlePloS one2018
Data collection and storage in long-term ecological and evolutionary studies: The Mongoose 2000 system.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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11 authors.
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Abstract
Studying ecological and evolutionary processes in the natural world often requires research projects to follow multiple individuals in the wild over many years. These projects have provided significant advances but may also be hampered by needing to accurately and efficiently collect and store multiple streams of the data from multiple individuals concurrently. The increase in the availability and sophistication of portable computers (smartphones and tablets) and the applications that run on them has the potential to address many of these data collection and storage issues. In this paper we describe the challenges faced by one such long-term, individual-based research project: the Banded Mongoose Research Project in Uganda. We describe a system we have developed called Mongoose 2000 that utilises the potential of apps and portable computers to meet these challenges. We discuss the benefits and limitations of employing such a system in a long-term research project. The app and source code for the Mongoose 2000 system are freely available and we detail how it might be used to aid data collection and storage in other long-term individual-based projects.
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