RESUMEN
With growing demand for data reuse and open data within the scientific ecosystem, protecting the confidentialy of survey data and privacy of data subjects is increasingly important. Doing so requires more than legal procedures and technological controls; it requires social and behavioral intervention. In this research note, we delineate the disclosure risks of various types of survey data (e.g., longitudinal data, social network data, sensitive information, biomarkers, and geographic data), the current motivation for data reuse, and challenges to data protection. Despite rigorous efforts to protect data, there are still threats to protection of confidentiality in microdata. Unintentional data breaches, protocol violations, and data misuse are observed even in well-established restricted data access systems, indicating that the systems may all rely heavily on trust. Creating and maintaining that trust is critical to secure data access. We suggest four ways of building trust; User-Centered Design Practices; Promoting Trust for Protecting Confidential Data; General Training in Research Ethics; and Specific Training in Data Security Protocols, with an example of a new project 'Researcher Passport' by the Inter-university Consortium for Political and Social Research. Continuous user-focused improvements in restricted data access systems are necessary so that we promote a culture of trust among the research and data user community, train both in the general topic of responsible research and in the specific requirements of these systems, and offer systematic and holistic solutions.
RESUMEN
Many organizations across the world that manage restricted data have adapted the Five Safes framework (safe data, safe projects, safe people, safe setting, safe output) for their management of restricted and confidential data. While the Five Safes have been well integrated throughout the data life cycle, organizations encounter several challenges with regard to safe data management. In this paper, we review current practices for restricted data management, and discuss challenges and future directions. We focus on data use agreements, disclosure risk review, and training. In the future, organizations managing restricted data may need proactively to take into consideration reducing inequalities in access to scientific data, preventing unethical use of data, and managing various types of data.
RESUMEN
In 2010, ICPSR began a long process of recovering data from Gordon Streib's Cornell Study of Occupational Retirement (CSOR). Because these unique data fill a gap in our understanding of US retirement history, we determined that an extensive data recovery project was warranted. This paper describes the scope of the data collection and the steps in ICPSR's recovery process. Though the data recovery was ultimately successful, this paper documents the amount of time invested and costs associated with this kind of recovery work. It also highlights the value of these data for future research in understanding gender and retirement in a historic context. In addition to the resulting publicly available data arising from this project, extensive paper medical records are housed at ICPSR for on-site analysis or for a future digitization project. These data would provide unique health information on older women and men traced over a period of time in the 1950s and represents future work for ICPSR to undertake.