Ziggy: Characterizing Query Results for Data Explorers

Data exploration has received much attention during the last few years. The aim is to learn interesting new facts from a possibly unfamiliar data set. Typically, explorers operate by trial and error: they write a query, inspect the results and refine their specifications accordingly. In this demo proposal, we present Ziggy, a system to help them understand their query results. Ziggy's aim is to complement an existing exploration system. It assumes that users already have a query in mind, but they do not know what is interesting about it. To assist them, it detects characteristic views, that is, small sets of columns on which the tuples in the results are different from those in the rest of the database. Thanks to these views, our explorers can understand why their selection is unique and make more informed exploration decisions.