$\Upsilon$-DB: A system for data-driven hypothesis management and analytics
Abstract
The vision of -DB introduces deterministic scientific hypotheses as a kind of uncertain and probabilistic data, and opens some key technical challenges for enabling data-driven hypothesis management and analytics. The -DB system addresses those challenges throughout a design-by-synthesis pipeline that defines its architecture. It processes hypotheses from their XML-based extraction to encoding as uncertain and probabilistic U-relational data, and eventually to their conditioning in the presence of observations. In this demo we present a first prototype of the -DB system. We showcase its core innovative features by means of use case scenarios in computational science in which the hypotheses are extracted from a model repository on the web and evaluated (rated/ranked) as probabilistic data.
Cite
@article{arxiv.1411.7419,
title = {$\Upsilon$-DB: A system for data-driven hypothesis management and analytics},
author = {Bernardo Gonçalves and Frederico C. Silva and Fabio Porto},
journal= {arXiv preprint arXiv:1411.7419},
year = {2014}
}
Comments
6 pages, 7 figures, submitted to ACM SIGMOD 2015, Demo track. arXiv admin note: substantial text overlap with arXiv:1411.5196