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The vision of $\Upsilon$-DB introduces deterministic scientific hypotheses asa kind of uncertain and probabilistic data, and opens some key technicalchallenges for enabling data-driven hypothesis management and analytics. The$\Upsilon$-DB system addresses those challenges throughout adesign-by-synthesis pipeline that defines its architecture. It processeshypotheses from their XML-based extraction to encoding as uncertain andprobabilistic U-relational data, and eventually to their conditioning in thepresence of observations. In this demo we present a first prototype of the$\Upsilon$-DB system. We showcase its core innovative features by means of usecase scenarios in computational science in which the hypotheses are extractedfrom a model repository on the web and evaluated (rated/ranked) asprobabilistic data.

$\Upsilon$-DB: A system for data-driven hypothesis management and analytics