Research software engineering: Using a full-stack data science approach to empower research insights

Data accessibility is the linchpin in translating research into impact, as engagement from policymakers to the public is uplifted when stakeholders are freely able to interact with research data and become inspired at their own pace. However, there are significant challenges in making this information accessible and interactive: not only is there an incredible volume of data, interrogating this data in a simple way requires an incredibly rare gathering of expertise in data science, data engineering and software development. The core challenge is the need to embrace complexity, while distilling insights into a visual format that connects data with a wide diversity of stakeholder groups. Highly customised code-driven tools, built with open-source software, create an opportunity to bridge this gap. This presentation will explore how bespoke dashboards and R packages can be used to share, manage and communicate research and technical outputs. Using applied examples from human, animal and environmental health, we will showcase how complex science can be translated into operational intelligence to support day-to day decision making in a number of contexts.ABOUT THE AUTHORAn epidemiologist with a strong academic background, Petra Muellner's career has taken her all over the globe and all over the spectrum of human, animal and environmental health. Working as a consultant for the Food and Agricultural Organisation of the United Nations for over a decade and collaborating with a large number of research groups and policy makers she has learned to work within diverse environments and effectively bridge the gap between disciplines. She is passionate about connecting data and analytical models with people and making both research and the most complex of data accessible and easy to explore. -----For more information about the eResearch NZ / eRangahau Aotearoa conference, visit: https://eresearchnz.co.nz/