Reproduce '14. HPCA 2014

PROB: A tool for Tracking Provenance and Reproducibility of Big Data Experiments


Reproducibility of computations and data provenance are very important goals to achieve in order to improve the quality of one's research. Unfortunately, despite some efforts made in the past, it is still very hard to reproduce computational experiments with high degree of certainty. The Big Data phenomenon in recent years makes this goal even harder to achieve. In this work, we propose a tool that aids researchers to improve reproducibility of their experiments through automated keeping of provenance records.

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big data, learning, personalized medicine, provenance


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