Making an Agricultural Research Dataset FAIR: A case study of the Australian Drought Monitor Dataset
Francis Gacenga1, Duc-Anh An-Vo1, David Cobon1, Richard Young1, Jillian Jackson1 1University Of Southern Queensland, Springfield, QLD, Australia
Abstract
Agricultural research data have traditionally been difficult to publicly access and share due in part to ownership, commercial interest, multiparty contracts between researchers, research organisations and funding bodies, as well as diverse research methods data management practice.
In this presentation we discuss how the FAIR (Findable, Accessible, Interoperable and Reusable) and CARE data principles are applied to the Australian Drought Monitor dataset, a product developed as part of the Northern Australia Climate Program (NACP), a joint project funded by Meat and Livestock Australia, the Queensland Drought and Climate Adaptation Program and the University of Southern Queensland (UniSQ).
The Drought Monitor was identified by our team as having a useful and useable dataset that was inaccessible to other agricultural or natural hazards researchers. By applying FAIR principles to this product, a database of NetCDF (Network Common Data Form) files and its associated metadata record has been developed for access and use by all interested researchers. We present here a case study of the process on how we applied the FAIR principles to the Australian Drought Monitor dataset and enabled its re-use and re-purposing in the Australian Research Data Commons (ARDC) funded Agricultural Research Federation (AgReFed) Platform project.
Biography
Dr Francis Gacenga is UniSQ’s Senior Digital Research Advisor. He is an IT Service Manager and researcher with international experience as a practitioner and published researcher. He has undertaken research funded by the Australian Research Council (ARC), Australian Research Data Commons (ARDC) and recently a Soils Cooperative Research Centre (CRC) funded project.
Dr Duc-Anh An-Vo has been a multi-disciplinary computational modeller across different disciplines from engineering (mechanics and materials), sciences (climate and agriculture) and economics (natural resources and decision making). He has broadly combined the available data sources together with physical and mathematical models to tackle climate change challenges. He is applying computational sciences, climate sciences and economics toward better decision making in agriculture and society. He is one of the principal developers of the AgReFed Platform for transforming agricultural research by modelling and data analytics on “cloud”. His research works were funded by industries (GRDC, MLA, ARC in Australia), and international funders such as IKI.