The Data Science Institute (DSI) at Columbia University has awarded 2020 seed grants to research teams whose projects merge data science with traditional fields to solve pressing societal problems. DSI’s Seed Funds Program supports new collaborations to forge long-term relationships among faculty in different disciplines and use data science to transform all fields across Columbia.
To put data science in context, we present phases of the data life cycle, from data generation to data interpretation. These phases transform raw bits into value for the end user. Data science is thus much more than data analysis, e.g., using techniques from machine learning and statistics; extracting this value takes a lot of work, before and after data analysis. Moreover, data privacy and data ethics need to be considered at each phase of the life cycle.
Columbia University is co-organizing and hosting the 2019 New York Scientific Data Summit, a two-and-a-half day symposium to explore data-driven discovery and innovation in science and industry. The summit is scheduled for June 12-14 in Columbia’s Davis Auditorium,
“Pixel Approximate Entropy” technique quantifies visual complexity by providing a score that automatically identifies difficult charts; could help users in emergency settings to read data at a glance and make better decisions faster.