UMBC ebiquity
Tracking Provenance and Reproducibility of Big Data Experiments

Tracking Provenance and Reproducibility of Big Data Experiments

Tim Finin, 11:53am 8 February 2014

In the first Ebiquity meeting of the semester, Vlad Korolev will talk about his work on using RDF for to capture, represent and use provenance information for big data experiments.

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

10-11:30am, ITE346, UMBC

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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