The Practice of Reproducible Research
Case Studies and Lessons from the Data-Intensive Sciences
Herausgeber: Turek, Daniel; Kitzes, Justin; Deniz, Fatma
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"Understanding why science should be open is only the first step; the second is to actually do it. This wide-ranging new book shows how researchers from a variety of disciplines are translating general principles into specific improvements in their work that others can learn from and imitate. Everyone who is trying to squeeze insight out of data will learn something from it, and those who are trying to train the next generation of scientists will find it a rich source of examples and models for their students to emulate."--Greg Wilson, Cofounder of Software Carpentry, now Principal Consultant ...
"Understanding why science should be open is only the first step; the second is to actually do it. This wide-ranging new book shows how researchers from a variety of disciplines are translating general principles into specific improvements in their work that others can learn from and imitate. Everyone who is trying to squeeze insight out of data will learn something from it, and those who are trying to train the next generation of scientists will find it a rich source of examples and models for their students to emulate."--Greg Wilson, Cofounder of Software Carpentry, now Principal Consultant with Rangle.io "The integrity of scientific knowledge depends crucially on the reliability and reproducibility of our published results. But what happens if we don't even report enough information to allow our experiments to be repeated? This book offers practical solutions to enhance the reporting and validation of research."--Randy Schekman, Professor, Department of Molecular and Cell Biology, University of California, Berkeley, and Investigator, Howard Hughes Medical Institute
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