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Articulating common ground in cooperative work: content and process
It is indicated that in complex collaborative work, process common ground increases, thus diminishing the need for acts like information querying or strategy discussions about how to organize the collaborative activities.
Using a large projection screen as an alternative to head-mounted displays for virtual environments
An empirical study was conducted investigating differences in spatial knowledge learned for a virtual environment presented in three viewing conditions: head-mounted display, large projection screen, and desk-top monitor, finding no statistically significant difference was found.
Privacy Preserving GWAS Data Sharing
This work presents methods for releasing differentially private minor allele frequencies, chi-square statistics and p-values, and proposes a privacy-preserving method for finding genome-wide associations based on a differentiallyPrivate approach to penalized logistic regression.
Supporting common ground and awareness in emergency management planning: A design research project
We present a design research project on knowledge sharing and activity awareness in distributed emergency management planning. In three experiments we studied groups using three different prototypes,
Privacy-Preserving Data Sharing for Genome-Wide Association Studies
Methods are proposed which allow for the release of aggregate GWAS data without compromising an individual’s privacy, and in many ways totally bystep the debate on the validity of the claims by Homer et al.
Supporting content and process common ground in computer-supported teamwork
Distinct sets of measures show that that the prototype supported both content and process common ground, offsetting the costs imposed by the distributed setting, and draw implications for moving beyond current models of sharing and coordination.
Inference using noisy degrees: Differentially private $\beta$-model and synthetic graphs
The paper addresses shortcomings of current approaches to a fundamental problem of how to perform valid statistical inference from data released by privacy mechanisms, and lays a foundational groundwork on how to achieve optimal and private statistical inference in a principled manner by modeling the privacy mechanism.
General and specific utility measures for synthetic data
A previous general measure of data utility, the propensity score mean-squared-error (pMSE), is adapted to the specific case of synthetic data and derive its distribution for the case when the correct synthesis model is used to create the synthetic data.
Ten Simple Rules for the Care and Feeding of Scientific Data
Galileo's work advanced the “Scientific Revolution,” and his approach to observation and analysis contributed significantly to the shaping of today's modern “scientific method”.