Developing a modern data workflow for evolving data

• DOI: 10.1101/344804
• Publication Date: 2018-06-12T15:45:12Z
• Authors: Glenda M. Yenni; Erica M. Christensen; Ellen K. Bledsoe; Sarah R. Supp; Renata M. Diaz; Ethan P. White; S.K. Morgan Ernest
• Keywords: 0301 basic medicine; 03 medical and health sciences; Chiroptera; Mammalia; bats; Animalia; bat; Biodiversity; Chordata

AbstractData management and publication are core components of the research process. An emerging challenge that has received limited attention in biology is managing, working with, and providing access to data under continual active collection. “Evolving data” present unique challenges in quality assurance and control, data publication, archiving, and reproducibility. We developed a evolving data workflow for a long-term ecological study that addresses many of the challenges associated with managing this type of data. We do this by leveraging existing tools to: 1) perform quality assurance and control; 2) import, restructure, version, and archive data; 3) rapidly publish new data in ways that ensure appropriate credit to all contributors; and 4) automate most steps in the data pipeline to reduce the time and effort required by researchers. The workflow uses two tools from software development, version control and continuous integration, to create a modern data management system that automates the pipeline.