An in-depth examination of requirements for disclosure risk assessment.

The use of formal privacy to protect the confidentiality of responses in the 2020 Decennial Census of Population and Housing has triggered renewed interest and debate over how to measure the disclosure risks and societal benefits of the published data products. We argue that any proposal for quantifying disclosure risk should be based on prespecified, objective criteria. We illustrate this approach to evaluate the absolute disclosure risk framework, the counterfactual framework underlying differential privacy, and prior-to-posterior comparisons. We conclude that satisfying all the desiderata is impossible, but counterfactual comparisons satisfy the most while absolute disclosure risk satisfies the fewest. Furthermore, we explain that many of the criticisms levied against differential privacy would be levied against any technology that is not equivalent to direct, unrestricted access to confidential data. More research is needed, but in the near term, the counterfactual approach appears best-suited for privacy versus utility analysis.

Playing catch-up in building an open research commons.

As efforts advance around the globe, the US falls behind.

Examining the population level and individual level longitudinal stability of psychosocial measures in the US Army's Global Assessment Tool (GAT).

As a component of the US Army's Comprehensive Soldier and Family Fitness program (CSF2), the Global Assessment Tool (GAT) represents a multidimensional constellation of measures designed to assess characteristics related to resilience. Using a foundation of validated measures from prior research, the GAT has been the vehicle for self-assessment to provide Soldiers, their families, and Army Civilians snapshots of their psychosocial wellness. Despite the long history of the measurement instrument (first implemented in 2009) and widespread use (mandatory for all active-duty Soldiers annually), the longitudinal capabilities of the GAT has received little attention. Here, we examine the longitudinal stability of the GAT across an approximate five-year time frame and multiple statistical approaches that demonstrate measurement stability at both the aggregate population level (people on average) and the individual level. We find evidence that the majority of the measures within the GAT are relatively stable over time both at the population level and individual level. This evidence contributes to knowledge of how best to improve the GAT for future use with the pay-off for the Army being a self-assessment tool that is more effective and efficient.

Opportunities to observe and measure intangible inputs to innovation: Definitions, operationalization, and examples.

Measuring the value of intangibles is not easy, because they are critical but usually invisible components of the innovation process. Today, access to nonsurvey data sources, such as administrative data and repositories captured on web pages, opens opportunities to create intangibles based on new sources of information and capture intangible innovations in new ways. Intangibles include ownership of innovative property and human resources that make a company unique but are currently unmeasured. For example, intangibles represent the value of a company's databases and software, the tacit knowledge of their workers, and the investments in research and development (R&D) and design. Through two case studies, the challenges and processes to both create and measure intangibles are presented using a data science framework that outlines processes to discover, acquire, profile, clean, link, explore the fitness-for-use, and statistically analyze the data. The first case study shows that creating organizational innovation is possible by linking administrative data across business processes in a Fortune 500 company. The motivation for this research is to develop company processes capable of synchronizing their supply chain end to end while capturing dynamics that can alter the inventory, profits, and service balance. The second example shows the feasibility of measurement of innovation related to the characteristics of open source software through data scraped from software repositories that provide this information. The ultimate goal is to develop accurate and repeatable measures to estimate the value of nonbusiness sector open source software to the economy. This early work shows the feasibility of these approaches.