The foundational treaty of the global nuclear order, the Nuclear Non-Proliferation Treaty (NPT), does not define what constitutes a nuclear weapon and therefore what activities, technologies, and materials should be regarded as evidence that a state is seeking to acquire nuclear weapons. This lack of definition exacerbates the nonproliferation challenge of distinguishing between legitimate nuclear activities (be they peaceful or military applications such as naval propulsion) and illegitimate ones (namely, those oriented toward nuclear weapons). This challenge, in turn, exacerbates the difficulty of promoting the peaceful spread of nuclear energy while, at the same time, preventing weapons proliferation. This grant supports an initiative by the Carnegie Endowment for International Peace to build an international consensus around how to distinguish between legitimate and illegitimate nuclear activity. The Carnegie team will convene policymakers, regulators, and technical personnel from the five permanent member countries of the UN Security Council - China, France, Russia, the United Kingdom, and the United States - for a series of non-political meetings to discuss national perspectives on what constitutes illegitimate nuclear activity, weigh the costs and benefits of potential frameworks, and identify areas for further technical analysis.

Though few deny that administrative and other large-linked datasets represent new frontiers for social science research, there have been surprisingly few formal studies that survey and document how so-called "big data" in all its forms is actually changing social science research. This grant supports a project by a team led by Eric T. Meyer at Oxford's Internet Institute (OII) to empirically document the ways social scientists are getting access to data at scale and the tools they use to work with it. Meyer and his team will conduct a series of in-depth interviews with 125 researchers and technologists in academia, industry, and government to look at a series of interrelated questions about how big data is changing research, including how data flows between data sources and scientists, what questions big data is being used to address, how does the openness of a dataset affect its use, and how public and private data are used differently by researchers.