Privacy, Anonymity, and Big Data in the Social Sciences

Abstract

Open data has tremendous potential for science, but, in human subjects research, there is a tension between privacy and releasing high-quality open data. Federal law governing student privacy and the release of student records suggests that anonymizing student data protects student privacy. Guided by this standard, we de-identified and released a data set from 16 MOOCs (massive open online courses) from MITx and HarvardX on the edX platform. In this article, we show that these and other de-identification procedures necessitate changes to data sets that threaten replication and extension of baseline analyses. To balance student privacy and the benefits of open data, we suggest focusing on protecting privacy without anonymizing data by instead expanding policies that compel researchers to uphold the privacy of the subjects in open data sets. If we want to have high-quality social science research and also protect the privacy of human subjects, we must eventually have trust in researchers. Otherwise, we'll always have the strict tradeoff between anonymity and science illustrated here. The open in massive open online course has many interpretations. Some MOOCs are hosted on open-source platforms, some use only openly licensed content, and most MOOCs are openly accessible to any learner without fee or prerequisites. We would like to add one more notion of openness: open access to data generated by MOOCs. We argue that this is part of the responsibility of MOOCs, and that fulfilling this responsibility threatens current conventions of anonymity in policy and public perception. In this spirit of open data, on May 30, 2014, a team of researchers from Harvard and MIT (including this author team) announced the release of an open data set containing student records from 16 courses conducted in the first year of the edX platform. (In May 2012, MIT and Harvard launched edX, a nonprofit platform for hosting and marketing MOOCs. MITx and HarvardX are the two respective institutional organizations focused on MOOCs.) 6 The data set is a de-identified version of that used to publish HarvardX and MITx: The First Year of Open Online Courses, a report revealing findings about student demographics, course-taking patterns, certification rates, and other measures of student behavior. 6 The goal for this data release was twofold: first, to allow other researchers to replicate the results of the analysis; and second, to allow researchers to conduct novel analyses beyond the original work, adding to the body of literature about open online courses. Within hours of the release, original analysis of the data began appearing on Twitter, with figures and source code. Two weeks after the release, the data journalism team at The Chronicle of Higher Education published "8 Things You Should Know about MOOCs," an article that explored new dimensions of the data set, including the gender balance of the courses. 13 Within the first month of the release, the data had been downloaded more than 650 times. With surprising speed, the data set began fulfil...

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