Join the second session of the "Data Horror Stories: What Haunts Projects and How to Exorcise It" Seminar Series. This event is co-sponsored by Countway Library and HMS/HSDM Office for Postdoctoral Fellows.

You followed the protocol. You submitted the paperwork. You think you shared the right file.

But somewhere between good intentions and a rushed deadline, something went wrong. A spreadsheet with patient identifiers went to the wrong inbox. A dataset landed on a personal laptop. A repository went live before the embargo lifted. And suddenly, what started as a research project becomes a federal compliance issue, an institutional crisis, or worse - a headline.

Data security and privacy violations don't always look like malicious hacks or bad actors. More often, they look like an honest mistake made by a well-meaning researcher who didn't know what they didn't know. And in a landscape shaped by IRB regulations and increasingly strict federal data sharing requirements, not knowing can have serious consequences.

In the second session of our three-part series "Data Horror Stories: What Haunts Projects and How to Exorcise It" we venture into the darkest corner of the data lifecycle where privacy, security, and compliance collide. We'll walk through real-world cases drawn from the news and Harvard's own research community, examine what went wrong at every turn, and give you the tools to keep your research on the right side of the law, your IRB, and your participants' trust.

Meet Your Guides Through the Data Haunted House:

• Colleen Cressman, Librarian for Open Publishing, Harvard Library Open Scholarship and Research Data Services
• Leslie Howes, Director, Office of Regulatory Affairs & Research Compliance, HSPH
• Ingrid Skoog, Data Privacy and InfoSec Officer, FAS
• Caroline Wood, Associate Director of Research Data Compliance, HMS
• Dan Wainstock, Director for Research Integrity, HMS

This is a free 1 hour webinar via Zoom (link provided upon registration). This seminar is open to all Harvard affiliates from all disciplines, and the public research community. 

The scariest data stories aren't about monsters. They're about mistakes anyone could make - until now.