Restricted data management: the current practice and the future

Main Article Content

Joy Bohyun Jang
Amy Pienta
Margaret Levenstein
Joe Saul


Many restricted data managing organizations across the world 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 observe several unintended challenges regarding data being FAIR (Findable, Accessible, Interoperable, Reusable). In the current study, we review the current practice on the restricted data management and discuss challenges and future directions, especially focusing on data use agreements, disclosure risks review, and training. In the future, restricted data managing organizations may need to proactively take into consideration reducing inequalities in access to scientific development, preventing unethical use of data in their management of restricted and confidential data, and managing various types of data.

Article Details

How to Cite
Jang, Joy Bohyun, Amy Pienta, Margaret Levenstein, and Joe Saul. 2023. “Restricted Data Management: The Current Practice and the Future”. Journal of Privacy and Confidentiality 13 (2).
NAHDAP-ICPSR restricted data workshop


Alves, K., & Ritchie, F. (2020). Runners, repeaters, strangers and aliens: Operationalising efficient output disclosure control. Statistical Journal of the IAOS, 36(4), 1281-1293. DOI: 10.3233/SJI-200661

Desai, T., Ritchie, F., & Welpton, R. (2016). Five Safes: Designing data access for research.

Green, E., Ritchie, F., Newman, J., & Parker, T. (2017). Lessons learned in training ‘safe users’ of confidential data. Worksession on Statistical Data Confidentiality.

Griffiths, E., Greci, C., Kotrotsios, Y., Parker, S., Scott, J., Welpton, R., ... & Woods, C. (2019). Handbook on statistical disclosure control for outputs. Safe Data Access Professionals Working Group.

Levenstein, M. C. (2019). Managing Research and Data for Reproducibility and Transparency.

Levenstein, M. C. (2020). Addressing Challenges of Restricted Data Access.

Levenstein, M.C., Tyler, A.R.B., & Davidson Bleckman, J. (2018). The Researcher Passport: Improving Data Access and Confidentiality Protection: ICPSR’s Strategy for a Community-normed System of Digital Identities of Access. ICPSR White Paper Series, Ann Arbor, MI: University of Michigan Inter-university Consortium for Political and Social Research.

OECD (2015), "Making Open Science a Reality", OECD Science, Technology and Industry Policy Papers, No. 25, OECD Publishing, Paris,

O’Hara, A. (2020). “Model Data Use Agreements: A Practical Guide.” In: Cole, Dhaliwal, Sautmann, and Vilhuber (eds), Handbook on Using Administrative Data for Research and Evidence-based Policy. Accessed at on 2022-11-15.

Palmiter, S., Elkerton, J., & Baggett, P. (1991). Animated demonstrations vs written instructions for learning procedural tasks: a preliminary investigation. International Journal of Man-Machine Studies, 34(5), 687-701.

Ritchie, F. (2017). The `Five Safes': a framework for planning, designing and evaluating data access solutions. Data For Policy Conference.

Ritchie, F., Green, E., & Smith, J. (2021). Automatic Checking of Research Outputs (ACRO): a tool for dynamic disclosure checks. EUROSTAT Statistical Working Paper. DOI: 10.2785/75954

Stocchi, M. & Bujnowska, A. (2021). Automatic checking of research outputs.

UNESCO. (2021). UNESCO recommendation on open science.