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

dc.contributor.authorKorolev, Vladimir
dc.contributor.authorJoshi, Anupam
dc.date.accessioned2018-11-02T14:16:56Z
dc.date.available2018-11-02T14:16:56Z
dc.date.issued2014-03-02
dc.descriptionReproduce '14. HPCA 2014en
dc.description.abstractReproducibility 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.en
dc.description.urihttps://ebiquity.umbc.edu/paper/html/id/650/PROB-A-tool-for-Tracking-Provenance-and-Reproducibility-of-Big-Data-Experimentsen
dc.format.extent6 pagesen
dc.genreconference papers and proceedings pre-printen
dc.identifierdoi:10.13016/M2R20S123
dc.identifier.urihttp://hdl.handle.net/11603/11837
dc.language.isoenen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectTrackingen
dc.subjectReproducibilityen
dc.subjectBig Dataen
dc.subjectcomputationsen
dc.subjectdata provenanceen
dc.subjectUMBC Ebiquity Research Groupen
dc.titlePROB: A tool for Tracking Provenance and Reproducibility of Big Data Experimentsen
dc.typeTexten

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