This class is on research design and research methods related to confidential information. In this class we’ll discuss how to recognize sensitive information; prepare for IRB review; reduce risks in data collection; evaluate information threats and vulnerabilities; organize and store sensitive data; understand data use agreements; and create data management plans. If you’re a researcher, whether a late career grad student, faculty, or professional research staff, this class is for you.
Much of the web remains invisible: resources are undescribed, unindexed or simply buried -- as many people rarely look past the first page of Google searches or are unavailable from traditional library resources.
At the same time many traditional library databases pay little attention to quality content from credible sources accessible on the open web.
Survey costs are increasing and response rates are decreasing. These pressures are forcing official statistical agencies to re-examine the way they collect data. Big Data are potential drivers of innovation that may reduce survey costs and respondent burden, but that also pose threats to inference and transparency. We need to understand how using big data, in conjunction with survey data collection, can address the issues posed by rising costs and nonresponse while producing transparent inference.
Based on mobile devices alone, commercial entities have the potential to collect extensive, fine grained, continuous, and identifiable records of a persons location and movement history, accompanied with a partial record of other mobile devices (potentially linked to people) encountered over that history. This information is increasingly used for commercial purposes, such as targeted advertising, and for scientific research. Read more about Location Confidentiality and Official Surveys -- Second Census-MIT Big Data Workshop