Implementing Reproducible Research

ISBN-13: 9780367576172 / Angielski / Miękka / 2020 / 448 str.

Victoria Stodden; Friedrich Leisch; Roger D. Peng

Opis

This work covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science. Each part presents contributions

Spis treści

Tools: knitr: A Comprehensive Tool for Reproducible Research in R. Reproducibility Using VisTrails. Sumatra: A Toolkit for Reproducible Research. CDE: Automatically Package and Reproduce Computational Experiments. Reproducible Physical Science and the Declaratron. Practices and Guidelines: Developing Open-Source Scientific Practice. Reproducible Bioinformatics Research for Biologists. Reproducible Research for Large-Scale Data Analysis. Practicing Open Science. Reproducibility, Virtual Appliances, and Cloud Computing. The Reproducibility Project: A Model of Large-Scale Collaboration for Empirical Research on Reproducibility—Open Science Collaboration. What Computational Scientists Need to Know about Intellectual Property Law: A Primer. Platforms: Open Science in Machine Learning. RunMyCode.org: A Research-Reproducibility Tool for Computational Sciences. Open Science and the Role of Publishers in Reproducible Research. Index.

O autorze

Victoria Stodden