Privacy Tools for Sharing Research Data
Information technology, advances in statistical computing, and the deluge of data available through the Internet are transforming social science. With the ability to collect and analyze massive amounts of data on human behavior and interactions, social scientists can hope to uncover many more phenomena, with greater detail and confidence, than allowed by traditional means such as surveys and interviews. However, a major challenge for computational social science is maintaining the privacy of human subjects. Beyond harm that may be suffered by the subjects themselves, privacy violations are a serious threat to the future of computational social science research.
Led collaboratively by Harvard University's Center for Research on Computation and Society (CRCS) at the School of Engineering and Applied Sciences, Institute for Quantitative Social Science (IQSS), and Berkman Center for Internet & Society, with support from the Secure and Trustworthy Cyberspace (SaTC) program at the National Science Foundation, the Privacy Tools for Sharing Research Data project seeks to develop methods, tools, and policies to further the tremendous value that can come from collecting, analyzing, and sharing data while more fully protecting individual privacy.
Executive Director and Harvard Law School Professor of Practice Urs Gasser leads the Berkman Center's role in this exciting initiative, which brings the Center's institutional knowledge and practical experience to help tackle the legal and policy-based issues in the larger project. The Berkman Center is working with Berkman faculty, fellows, research assistants, and the CRCS and IQSS project team members to distill key definitional issues, explore new and existing legal and regulatory frameworks, and develop legal instruments that take into account the specific needs of researchers, research subjects, and data, while enabling reliable mechanisms for protecting privacy, transparency, and accountability.
This material is based upon work supported by the National Science Foundation under Grant No. CNS-1237235. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.