Identifying Sensitive, Private, or Legally Protected Data in DRUM Submissions

Abstract

Identifying sensitive, private, or legally protected data is a prevalent issue that data repositories and archives are faced with today. Restricted information can be difficult to detect in large datasets, however there are numerous tools that can facilitate this process. This poster provides an overview of two tools that have extensive search and identification capabilities, namely Identity Finder and Bulk Extractor. The Data Repository for the University of Minnesota (DRUM) utilizes these tools to ensure that all submissions are free of restricted data. The workflow for evaluation and review of DRUM submissions was created using these tools and is also presented here. Additionally, the nineteen personal identifiers, defined by the HIPAA Privacy Rule, are listed with corresponding examples and procedures for identification.