Application and Evaluation of the Hoffman et al. (2020) Data Rescue Framework using an historic Scottish Cloud and Rain Chemistry Dataset exemplar - Shona Ferguson; John Cape; Alan Crossley; Frank Harvey; David Fowler; David Leaver; Christine Braban (International Journal of Digital Curation)
Environmental data are vitally important and valuable research outputs, and there are vast quantities in laboratory storage and on servers where they are not easily or openly accessible. It is imperative for preservation and for potential reuse purposes that historical data of long-term value are efficiently curated and made publicly available. We evaluated the Hoffman et al. (2020) data rescue framework (DRF) for the initial assessment stage of a data rescue by applying it to an historic Scottish cloud and rain chemistry dataset. The DRF facilitated workload prioritisation, anticipating potential obstacles, and approximating resources required. We used a novel points-based adaptation of the DRF to identify suitability of datasets for rescue and compare the dataset status before and after rescue, particularly taking FAIR principles into account. The reusability of the dataset was greatly improved by the Hoffman et al. (2020) framework, and it is now published in an appropriate open access data centre with detailed metadata. It is recommended that the traceable DRF and scoring system be adopted in future to begin moving twentieth and early twenty-first century environmental data into the public domain.