John Erickson, of the Institute for Data Exploration and Applications (IDEA) at Rensselear Polytechnic Institute (RPI), is the lead engineer of COVIDMINDER--a graph and map-based visualization tool for COVID-19 statistics across the nation, by state and by county, with daily updates. COVIDMINDER is an outgrowth from MORTALITYMINDER which graphs and maps the demographics of mortality disparities. These projects are under the Health INCITE program at RPI with Dr. Kristen Bennett, and is funded by the United Health Foundation. Go online (now!) and check out the COVIDMINDER web application at "covidminder.idea.rpi.edu" and the related MORTALITYMINDER at "mortalityminder.idea.rpi.edu".
Podcasts and Videos
Plan to join us for a very, VERY special TWed as the Tetherless World Constellation holds a "virtual" version of our end-of-term Graduate Research "Lightning Talks." TWed Lightning Talks are a great way for the TWC community and friends to learn of the wide range of amazing research happening in the Tetherless World, and "a good time is had by all!"
Attempting to use real medical data in a classroom setting is hard to do without limiting yourself to specific datasets. Through the research being presented we work to create an end-to-end workflow for generating synthetic health data and testing the synthetic data for privacy, resemblance, and utility. This includes creating a novel generation method called HealthGAN and defining metrics for measuring the privacy and resemblance of the generated data. The utility of the data is then measured in the context of the analysis task the dataset was designed to accomplish. The workflow is then tested by attempting to create synthetic versions of two real medical datasets from a secure environment.
COVIDMINDER examines how and why COVID-19 impacts regions differently. Using daily updated data, COVIDMINDER compares community risks, mediation tools, and outcomes related to COVID-19 by state across the United States, and by county within New York state.
TWed Talk: Minor Gordon on "A clean architecture for semantic web applications"
User expectations of modern web applications continue to outpace the productivity of the software engineering process. The semantic web application stack of RDF, SPARQL, and related technologies, provides many benefits to users and developers, at the expense of additional complexity that impedes the engineering process. I will present a new software architecture that attempts to maximize the user-visible benefits of these technologies while minimizing their impact on developer productivity. I will also discuss an implementation of the architecture using off-the-shelf tools, such as TypeScript, GraphQL, and Scala, in conjunction with semantic web technologies. The result serves as a vehicle for delivering bespoke web applications for sponsored research projects, incorporating research into symbolic artificial intelligence, and helping students learn modern software engineering.
Twed Talk: What's a Personal (Health) Knowledge Graph?
Recent years have seen a rising interest in combining the rich structured information contained in knowledge graphs with applications involving personalization. This talk will discuss insights into the emerging topic of "personal knowledge graphs", including key research challenges identified in literature and examples of proposed personal knowledge graph systems (especially in the domain of personalized health).