| dc.description.abstract | Camera traps are a widely used tool to study and monitor biodiversity, benefiting researchers as well as the community at large, including park rangers, nature reserve owners, and conservation stakeholders. These monitoring efforts generate large volumes of data of value to science, contributing to the understanding of biodiversity, especially mammals. However, the complexity associated with the processing and analysis of this information is evident, since it requires technical knowledge of taxonomy and format management skills, hindering its publication on platforms such as the Global Biodiversity Information Facility (GBIF) and the Biodiversity Information System (SIB Colombia). Recognizing the importance of disseminating camera trap data for biodiversity management, we propose a workflow in R for processing these data efficiently, without the need for in-depth taxonomic knowledge and automating the generation of the Darwin Core format (Dwc). In contrast to other tools available for biodiversity data processing, our proposal focuses on promoting and simplifying the publication of data by the academic community and non-academic actors, guaranteeing the technical quality of the data, the accuracy of the taxonomy used and reducing the time required to fill out forms for publication. To validate the most efficient management in terms of reducing the time spent in processing biodiversity data, a dataset obtained in El Globo Natural Reserve (Támesis, Antioquia) was used. From the results obtained in an experimental test with a total of 10 expert and non-expert volunteers, it is concluded that the implementation of the workflow allows a reduction in the time spent in data processing and the completion of the DwC format. In addition to speeding up the process, this automation reduces the workload and potentially reduces errors in completing the form. | |
