Visualizing database queries
Manasi Vartak · DSpace@MIT (Massachusetts Institute of Technology) · 2014
Data analysts operating on large volumes of data often rely on visualizations to in-terpret the results of queries. However, finding the right visualization for a query is a laborious and time-consuming task. We propose SEEDB, a system that partially automates this task: given a query, SEEDB explores the space of all possible visualiza-tions, and automatically identifies and recommends to the analyst those visualizations it finds to be most "interesting " or "useful".