Martin O’Reilly, Turing Institute
Researchers frequently encounter a need for: – Secure environments for analysis of sensitive datasets – A productive environment for curiosity-driven research – High performance computing capability Achieving all the above while striking the right balance between the security of the data and the productivity of the research environment is difficult to achieve within many existing secure research environments (Safe Havens). The Alan Turing Institute has been developing recommended policies and controls for performing productive research on sensitive data, as well as a cloud-based Safe Haven to implement these in practice. This comprises: – A shared model for classifying data sets and projects into common sensitivity tiers, with recommended security measures for each tier and a web-based tool to support this process. – A cloud-based Safe Haven implementation using software defined infrastructure to support the reliable and efficient deployment of project specific secure research environments tailored to the agreed sensitivity tier for the project. – The availability of a productive environment for curiosity-driven research within the Safe Haven, including easy access to a wide range of data science software packages and community provided code. – Support for the flexible deployment of specialised compute resources such as clusters or GPUs within the Safe Haven.