Documentation of sample collection and instrument deployment in the field is time-consuming, error-prone and laborious. Even though best practices in research data management suggest that data should be captured in a structured digital format as early as possible in the data life cycle, fieldwork often suffers a digitisation bottleneck.
Mobile applications are one solution to overcome the digitisation bottleneck. They allow data capture in the field, including automatic capture of contextual data like campaign information, operator, date and time, geographic position, etc. On the other hand, systematic field campaigns commonly follow specific workflows and no single application can cover all requirements. Development costs of creating a new software package for each field campaign are also prohibitive.
Instead of a specific mobile application, we use the FAIMS application framework that allows fast production of mobile data acquisition applications that are tailor-made for their intended use cases. In field deployments, we demonstrated that in combination with machine-readable sample labels the sample documentation workflow could be streamlined and the time needed could be reduced by 50%.
The FAIMS application framework allows data, collected offline, to be synchronised between devices and a server, facilitating both data sharing between campaign participants and securing against data loss. The collation of data in this manner also allows data to be fed back into field operations to support decision-making, e.g., to optimise sampling strategies in a dynamic environment or based on newly acquired data.
Jens Klump1, Shawn Ross2, Nathan Reid1, Brian Ballsun-Stanton2, Steve Cassidy2, Penny Crook2, Ryan Noble1, Adéla Sobotkova3
1CSIRO, Perth, Australia; 2Macquarie University, Sydney, Australia; 3Aarhus University, Aarhus, Denmark