The book The Practice of Reproducible Research: Case Studies and Lessons from the Data-Intensive Sciences - edited by BIDS research fellows Justin Kitzes, Daniel Turek, Fatma Deniz; and previously released in an free online version earlier this year;- will be released in print on October 17, 2017.
The book is the product of several years of effort by a team of authors from the Moore-Sloan Data Science Environments at UC Berkeley, the University of Washington, and New York University; whose main goal was to collect concrete examples of reproducible research "in the field," focusing on how scientists and engineers working in the data-intensive sciences actually organize their work to try to meet the goals of reproducibility.
The book itself is centered around a collection of 31 such examples of contributed case studies in reproducible research practices. Each case study presents the specific approach that the author used to achieve reproducibility in a real-world research project, including a discussion of the overall project workflow, major challenges, and key tools and practices used to increase the reproducibility of the research. Accompanying these case studies are several summary chapters (found in Part I of the book) that provide general lessons on reproducible research and synthesize common "lessons learned" and "pain points" from across the individual case study chapters.