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The practice of reproducible research: case studies and lessons from the data-intensive sciences

The Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. In each of the thirty-one case studies in this volume, the author or team describes the workflow that they used to...

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Detalles Bibliográficos
Autores principales: Kitzes, Justin, Turek, Daniel, Deniz, Fatma
Lenguaje:eng
Publicado: University of California Press 2017
Materias:
Acceso en línea:http://cds.cern.ch/record/2291943
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author Kitzes, Justin
Turek, Daniel
Deniz, Fatma
author_facet Kitzes, Justin
Turek, Daniel
Deniz, Fatma
author_sort Kitzes, Justin
collection CERN
description The Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. In each of the thirty-one case studies in this volume, the author or team describes the workflow that they used to complete a real-world research project. Authors highlight how they utilized particular tools, ideas, and practices to support reproducibility, emphasizing the very practical how, rather than the why or what, of conducting reproducible research.   Part 1 provides an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies themselves. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible.
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spelling cern-22919432021-04-21T19:01:43Zhttp://cds.cern.ch/record/2291943engKitzes, JustinTurek, DanielDeniz, FatmaThe practice of reproducible research: case studies and lessons from the data-intensive sciencesScience in GeneralThe Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. In each of the thirty-one case studies in this volume, the author or team describes the workflow that they used to complete a real-world research project. Authors highlight how they utilized particular tools, ideas, and practices to support reproducibility, emphasizing the very practical how, rather than the why or what, of conducting reproducible research.   Part 1 provides an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies themselves. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible.University of California Pressoai:cds.cern.ch:22919432017-10-17
spellingShingle Science in General
Kitzes, Justin
Turek, Daniel
Deniz, Fatma
The practice of reproducible research: case studies and lessons from the data-intensive sciences
title The practice of reproducible research: case studies and lessons from the data-intensive sciences
title_full The practice of reproducible research: case studies and lessons from the data-intensive sciences
title_fullStr The practice of reproducible research: case studies and lessons from the data-intensive sciences
title_full_unstemmed The practice of reproducible research: case studies and lessons from the data-intensive sciences
title_short The practice of reproducible research: case studies and lessons from the data-intensive sciences
title_sort practice of reproducible research: case studies and lessons from the data-intensive sciences
topic Science in General
url http://cds.cern.ch/record/2291943
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