Confidential Research Information Management: Security and Privacy Key Concepts
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This tutorial provides a framework for identifying and managing confidential information in research. It is most appropriate for mid-late career graduate students, faculty, and professional research staff who actively engage in the design/planning of research. The course will provide an overview of the major legal requirements governing confidential research data; and the core technological measures used to safeguard data. And it will provide an introduction to the statistical methods and software tools used to analyze and limit disclosure risks.
Failures of confidentiality threaten research integrity, reputation, legality, and funding. Every researcher in the social, behavioral and health sciences must understand how to manage confidential information in research. Successful management of confidential information is particularly challenging because it requires satisfying a combination of complex legal, statistical and technological constants. And the management of this information has grown increasingly challenging because of recent changes in the law, new forms of data collection, and advances in statistical methods for linking data.
The course will be presented in a half-day format. Individual consultations may be scheduled with Dr. Altman by contacting Kelly Hopkins at khopkins@mit.edu.
Discussant Bio: Dr. Micah Altman is Director of Research and Head/Scientist, Program on Information Science for the MIT Libraries, at the Massachusetts Institute of Technology. Dr. Altman is also a Non-Resident Senior Fellow at The Brookings Institution. Prior to arriving at MIT, Dr. Altman served at Harvard University for fifteen years as the Associate Director of the Harvard-MIT Data Center, Archival Director of the Henry A. Murray Archive, and Senior Research Scientist in the Institute for Quantitative Social Sciences.
Dr. Altman conducts work primarily in the fields of social science, information privacy, information science and research methods, and statistical computation—focusing on the intersections of information, technology, privacy, and politics; and on the dissemination, preservation, reliability and governance of scientific knowledge.
- Date:
- Monday, January 11, 2016
- Time:
- 1:00pm - 3:00pm
- Location:
- E25-401
- Categories:
- Classes & workshops