Findable, accessible, interoperable, and reusable
To realize the potential of data sharing, science needs to be redesigned for the digital age; we want to make it easy to apply increasingly sophisticated techniques like machine learning to improve the work of policy influencers and researchers. These changes need to simultaneously respect people's privacy and make (meta)data FAIR—findable, accessible, interoperable, and reusable. Since 2013, Ki has been building a data repository to help the Gates Foundation’s program teams generate knowledge. This work has demonstrated the value of data sharing, but this kind of painstakingly curated, in-house resource is not the end goal. We hope that all data will be available to the entire community of researchers in near-real-time so they can use all the information and tools that exist to maximize life-saving knowledge. To do this requires fundamental changes in the ways data is collected, managed, shared, protected, discovered, and accessed. We have started this journey by sharing Ki-developed tools like Study Explorer to encourage others to generate additional hypotheses. We continue to investigate means to further promote data sharing and standards among repositories beyond that of Ki, which we believe will ultimately facilitate greater global health collaboration.