Selected Upcoming Events
From the DataLab
Augmented Reality (AR) Sandbox
Developed at UC Davis, the AR Sandbox brings big concepts of the earth sciences to life for elementary- to college-aged students and faculty researchers. This hands-on exhibit features real sand, a Microsoft Kinect 3D camera, a data projector, and open source simulation and visualization software. As users mold the sand, it is augmented in real time by an elevation color map, topographic contour lines, and simulated water (or lava!) allowing for the exploration of topographic maps and models. The goal of the AR Sandbox is to teach geographic, geologic, hydrologic, and vulcanic concepts—from assessing the meaning of a watershed to reading maps.
From working with the United Nations to crossing computational science with statistics in his research, Martin Hilbert’s work has a broad impact. Martin still frequently works with the UN, conducting consultancy work for their human development report every year and bringing groups of students from UC Davis to Chile to harvest data by conducting webscraping projects for the organization. And though they couldn’t travel during the pandemic, Martin and his students worked with the UN to analyze the digital footprint of society’s migration online to better understand the labor market dynamics of a highly virtual world: “all of that you can do with data science,” he explains.
As a sociologist of work, Savannah Hunter researches issues of job quality: worker experience, health and safety, and how irregular hours and scheduling affect low-wage and hourly workers. Working with data is challenging in these areas, because there is often a lack of quality data; so part of Savannah’s job is to make good use of what’s available in order to inform the public debate around low-wage work and support organizations that assist workers in achieving good quality jobs. She considers her time working with DataLab during her PhD, where she learned to use data science tools and methods and collaborated across disciplines on meaningful data-driven projects, extremely valuable for her career.