An Integrated System for Accessing Large-Scale, Confidential Social Science Data

Project Summary

Large-scale databases from the social, behavioral, and economic sciences offer enormous potential benefits to society. However, as most stewards of social science data are acutely aware, wide-scale dissemination of such data can result in unintended disclosures of data subjects' identities and sensitive attributes, thereby violating promises–and in some instances laws to protect data subjects' privacy and confidentiality. 

Themes and Categories
Jerry Reiter
Statistical Science

Supported by a grant from the National Science Foundation Data Infrastructure Building Blocks program, we are developing an integrated system for disseminating large-scale social science data. The system includes:

(i) Capability to generate highly redacted, synthetic data intended for wide access, coupled with

(ii) Means for approved researchers to access the confidential data via secure remote access solutions, glued together by

(iii) A verification server that allows users to assess the quality of their analyses with the redacted data so as to be more efficient with their use of remote data access.

Related People

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In this two-day, virtual data expedition project, students were introduced to the APIM in the context of stress proliferation, linked lives, the spousal relationship, and mental and physical health outcomes.

Stress proliferation is a concept within the stress process paradigm that explains how one person’s stressors can influence others (Thoits 2010). Combining this with the life course principle of linked lives explains that because people are embedded in social networks, stress not only can impact the individual but can also proliferate to people close to them (Elder Jr, Shanahan and Jennings 2015). For example, one spouse’s chronic health condition may lead to stress-provoking strain in the marital relationship, eventually spilling over to affect the other spouse’s mental health. Additionally, because partners share an environment, experiences, and resources (e.g., money and information), as well as exert social control over each other, they can monitor and influence each other’s health and health behaviors. This often leads to health concordance within couples; in other words, because individuals within the couple influence each other’s health and well-being, their health tends to become more similar or more alike (Kiecolt-Glaser and Wilson 2017, Polenick, Renn and Birditt 2018). Thus, a spouse’s current health condition may influence their partner’s future health and spouses may contemporaneously exhibit similar health conditions or behaviors.

However, how spouses influence each other may be patterned by the gender of the spouse with the health condition or exhibiting the health behaviors. Recent evidence suggests that a wife’s health condition may have little influence on her husband’s future health conditions, but that a husband’s health condition will most likely influence his wife’s future health (Kiecolt-Glaser and Wilson 2017).

Stats/Sociology major Mitchelle Mojekwu joined Neuroscience majors Kassie Hamilton and Zineb Jaidi in a ten-week exploration of data relevant to an upcoming public school zone redistricting in Durham County. Using information acquired from the General Social Survey and the US Census, the team applied modern mathematical and statistical methods for generating proposed redistricting plans, with the aim of providing decision-makers with information they can use to produce school districts that are equitable and reflective of the Durham County student population.

View the team's project poster here

Watch the team's final presentation on Zoom:


Faculty Lead: Greg Herschlag

Project Manager: Bernard Coles


Shannon Houser (Stats/BioChem), Junbo Guan (MIDS), and Gaurav Sirdeshmukh (Stats) spent ten weeks exploring data concerning child and family health in Yolo County, CA. Using R Shiny, the team produced an interactive data dashboard that enables Yolo County residents to find healthcare and childcare providers, food resources, and transportation information.

View the team's project poster here

Watch the team's final presentation on Zoom:


Project Lead: Leigh Ann Simmons (UC Davis)