Open Science Collaboration Blog · Articles by Sean Mackinnon

"Nothing is really private anymore. Corporations like Facebook and Google have been collecting our information for some time, and selling it in aggregate to the highest bidder. People have been raising concerns over these invasions of privacy, but generally only technically-savvy, highly motivated people can really be successful at remaining anonymous in this new digital world. For a variety of incredibly important reasons, we are moving towards open research data as a scientific norm – that is, micro datasets and statistical syntax openly available to anyone who wants it. However, some people are uncomfortable with open research data, because they have concerns about privacy and confidentiality violations. Some of these violations are even making the news: A high profile case about people being identified from their publicly shared genetic information comes to mind. With open data comes increased responsibility. As researchers, we need to take particular care to balance the advantages of data-sharing with the need to protect research participants from harm. I’m particularly primed for this issue because my own research often intersects with clinical psychology. I ask questions about things like depression, anxiety, eating disorders, substance use and conflict with romantic partners. The data collected in many of my studies has the potential to seriously harm the reputation – and potentially the mental health – of participants if linked to their identity by a malicious person. This said, I believe in the value of open data sharing. In this post, I’m going to discuss a few core issues as it pertains to de-identification – that is, ensuring the anonymity of participants in an openly shared dataset. Violations of privacy will always be a risk: However, some relatively simple steps on the part of the researcher can make re-identification of individual participants much more challenging ..."