Mr. Quinten van der Leest1, Mr. Andy Allen2, Dr. Matt Garthwaite2, Dr. Georgina Wood3,5, Adj Prof. Melinda Coleman4, Dr. Tomas Remenyi1
1Eratos, Richmond, Australia, 2CSIRO, Aspendale, Australia, 3Flinders University, Adelaide, Australia, 4NSW Dept. of Primary Industries, Coffs Harbour, Australia, 5University of Western Australia, Perth, Australia
Biography:
Inspired by the endless potential of data to assist in explaining the unknown, Quinten aspires to further his expertise in data science. A self-motivated learner with creative problem solving and quantitative skills, Quinten thrives in an environment where he is allowed to push the boundaries of what is possible.
Abstract:
Research by its very nature is often on the leading edge of the possible. Thus, keeping pace with these aspirations of the research community is an ongoing challenge for the organisations that host these teams. In this presentation, we will present two case studies that describe solutions that have enabled researchers to increase their speed-to-value, rapidly progressing their projects such that valuable research outputs are visible, shareable and consumable by their colleagues and communities. The first case study is the Australian Satellite Calibration and Validation Data Hub project (AusCalVal). Satellite data is only as useful as its verifiable accuracy. The varied Australian landscape is used to provide the Calibration and Validation (CalVal) products used by the global community. The AusCalVal project aims: to prototype a metadata structure for CalVal products that inform data's verifiable quality, applicable across many semantically different sites and observations and linked to the Open Geospatial Consortium standard; and create a hub where both the data and metadata are available to users and operators in one place for all CalVal Sites in Australia. Eratos is the platform enabling this effort. The second case study is the Reef Adapt project. The Reef Adapt tool allows those wishing to conduct reef regeneration activities to select stock-sampling locations based on current or future climate conditions. Eratos assisted a small research team to operationalise their R-Shiny tool into a standalone web application deployable on AWS and accessible by the public. We will present how these approaches are transferable to other teams.