FAIR Data: Its all fun and games until someone uses a “I”.
FAIR Data (Findable, Accessible, Interoperable, Re-usable) is seen as a route to releasing value from our existing data in AstraZeneca as well as setting us up to be able to do so more easily with new data we generate from here on. As we look into the dimensions of FAIR data, Findability can be addressed by indexing and cataloguing our data, accessibility by a combination of information classification, automation and manual processes (including understanding informed consent from patients/participants) and re-usability can be supported by provisioning processes into approved analytical environments.
These are all significant challenges, with significant opportunities offered through optimisation and standardisation of supporting processes, but the biggest challenge of all is interoperability. Interoperability requires us to know whether two datasets of the same data type can be pooled for analytical purposes and how we can join together datasets of different types to answer complex questions.
In this talk, I will show how AZ R&D is approaching the challenges of Interoperability to enhance the re-use of our data.