Harvesting the Power of Big Data in Agriculture
Harvesting data and harvesting crops? There’s an app for that.
Tag: big data
Big data refers to a collection of data sets so large and complex that that they are difficult to process using available database management tools or traditional data processing applications. WID researchers are making transformative contributions to the mathematical and theoretical underpinnings of tools for analyzing massive data sets.
Big data is an important component of WID’s Data Science Hub.
A World of Math: WID Researcher Jordan Ellenberg on “How Not To Be Wrong”
Math’s everywhere — at least that’s the message from Discovery Fellow Jordan Ellenberg in his new book “How Not To Be Wrong.” Read a conversation with him on math’s impact on our lives, from science to religion.
WID and New York Hall of Science Team Collects Museum Data to Drive Learning and Collaboration Research
WID and the New York Hall of Science team up to collect data on learning and games.
Students Showcase Wearable Computing Projects, Design Thinking
What if clothing could respond to its environment? That’s the idea behind a transdisciplinary class offered by WID and School of Human Ecology researchers.
Printing without Boundaries: Transdisciplinary Partnerships Expand Uses for 3D Printers
Four different disciplines, four different uses of 3D printers. WID collaborators provide a glimpse into the revolutionary, unusual and downright cool ways 3D printing is influencing all types of research.
Closing the Loop on Big Data… One Beer at a Time
WID researchers develop algorithms for many applications and industries, but one side project boasts a more playful goal: Mapping brew preferences.
Tools for Discovery: Jordan Ellenberg
UW–Madison Mathematics Professor and Discovery Fellow Jordan Ellenberg provides perspective on programming in math, Google Hangout and why our brains are the ultimate tool for discovery.
Tackling ‘Netflix Problem,’ WID Researcher Snags Lagrange Prize
What do math and movies have in common? WID researcher Ben Recht explains how incomplete data sets and the “Netflix problem” aren’t that different after all.