Be the first to like this
Traditionally, natural sciences have predominantly leveraged High Performance Computing (HPC) infrastructure within academic environments, where significant computational resources have enabled astronomers to engage in the simulation modeling of stars and galaxies, or physicists to study proton- proton collisions. With the emerging use of HPC for social and health sciences, additional controls must be implemented to ensure compliance with legislative, institutional and ethical frameworks that govern sensitive research data. Often robust security measures are considered as a suitable response for managing the additional constraints presented by this paradigm shift. This approach is not sufficient as systems originally developed to support non-sensitive data must be re-designed to effectively embed privacy and ethical requirements – which is a necessary and often daunting task.
Drawing from experience at a provincial and national level, this presentation by Kaitlyn Gutteridge, Research Data Privacy and Security Officer at the University of British Columbia, considers cross-cutting privacy and ethical requirements throughout the research data lifecycle including data sovereignty and governance, data sharing and linkage, and the informed consent process. Best practices and examples of how organizations and institutions are embracing this challenge are put forward.