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Implementing Reproducible Research
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Book Synopsis Implementing Reproducible Research by : Victoria Stodden
Download or read book Implementing Reproducible Research written by Victoria Stodden and published by CRC Press. This book was released on 2018-12-14 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research 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. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org.
Book Synopsis Implementing Reproducible Research by : Victoria Stodden
Download or read book Implementing Reproducible Research written by Victoria Stodden and published by . This book was released on 2014-01-01 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research 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. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org.
Book Synopsis Reproducible Research with R and RStudio by : Christopher Gandrud
Download or read book Reproducible Research with R and RStudio written by Christopher Gandrud and published by CRC Press. This book was released on 2020-02-21 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for previous editions: "Gandrud has written a great outline of how a fully reproducible research project should look from start to finish, with brief explanations of each tool that he uses along the way... Advanced undergraduate students in mathematics, statistics, and similar fields as well as students just beginning their graduate studies would benefit the most from reading this book. Many more experienced R users or second-year graduate students might find themselves thinking, ‘I wish I’d read this book at the start of my studies, when I was first learning R!’...This book could be used as the main text for a class on reproducible research ..." (The American Statistician) Reproducible Research with R and R Studio, Third Edition brings together the skills and tools needed for doing and presenting computational research. Using straightforward examples, the book takes you through an entire reproducible research workflow. This practical workflow enables you to gather and analyze data as well as dynamically present results in print and on the web. Supplementary materials and example are available on the author’s website. New to the Third Edition Updated package recommendations, examples, URLs, and removed technologies no longer in regular use. More advanced R Markdown (and less LaTeX) in discussions of markup languages and examples. Stronger focus on reproducible working directory tools. Updated discussion of cloud storage services and persistent reproducible material citation. Added discussion of Jupyter notebooks and reproducible practices in industry. Examples of data manipulation with Tidyverse tibbles (in addition to standard data frames) and pivot_longer() and pivot_wider() functions for pivoting data. Features Incorporates the most important advances that have been developed since the editions were published Describes a complete reproducible research workflow, from data gathering to the presentation of results Shows how to automatically generate tables and figures using R Includes instructions on formatting a presentation document via markup languages Discusses cloud storage and versioning services, particularly Github Explains how to use Unix-like shell programs for working with large research projects
Book Synopsis The Practice of Reproducible Research by : Justin Kitzes
Download or read book The Practice of Reproducible Research written by Justin Kitzes and published by Univ of California Press. This book was released on 2018 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309486165 Total Pages :257 pages Book Rating :4.3/5 (94 download)
Book Synopsis Reproducibility and Replicability in Science by : National Academies of Sciences, Engineering, and Medicine
Download or read book Reproducibility and Replicability in Science written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-10-20 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
Book Synopsis Development Research in Practice by : Kristoffer Bjärkefur
Download or read book Development Research in Practice written by Kristoffer Bjärkefur and published by World Bank Publications. This book was released on 2021-07-16 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University
Book Synopsis Implementing Reproducible Research by : Victoria Stodden
Download or read book Implementing Reproducible Research written by Victoria Stodden and published by CRC Press. This book was released on 2018-12-14 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research 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. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org.
Book Synopsis Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis by : Gabriele Meiselwitz
Download or read book Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis written by Gabriele Meiselwitz and published by Springer Nature. This book was released on 2020-07-10 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 12194 and 12195 constitutes the refereed proceedings of the 12th International Conference on Social Computing and Social Media, SCSM 2020, held as part of the 22nd International Conference, HCI International 2020, which was planned to be held in Copenhagen, Denmark, in July 2020. The conference was held virtually due to the COVID-19 pandemic. The total of 1439 papers and 238 posters have been accepted for publication in the HCII 2020 proceedings from a total of 6326 submissions. SCSM 2020 includes a total of 93 papers which are organized in topical sections named: Design Issues in Social Computing, Ethics and Misinformation in Social Media, User Behavior and Social Network Analysis, Participation and Collaboration in Online Communities, Social Computing and User Experience, Social Media Marketing and Consumer Experience, Social Computing for Well-Being, Learning, and Entertainment.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309392020 Total Pages :133 pages Book Rating :4.3/5 (93 download)
Book Synopsis Statistical Challenges in Assessing and Fostering the Reproducibility of Scientific Results by : National Academies of Sciences, Engineering, and Medicine
Download or read book Statistical Challenges in Assessing and Fostering the Reproducibility of Scientific Results written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2016-03-29 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Questions about the reproducibility of scientific research have been raised in numerous settings and have gained visibility through several high-profile journal and popular press articles. Quantitative issues contributing to reproducibility challenges have been considered (including improper data measurement and analysis, inadequate statistical expertise, and incomplete data, among others), but there is no clear consensus on how best to approach or to minimize these problems. A lack of reproducibility of scientific results has created some distrust in scientific findings among the general public, scientists, funding agencies, and industries. While studies fail for a variety of reasons, many factors contribute to the lack of perfect reproducibility, including insufficient training in experimental design, misaligned incentives for publication and the implications for university tenure, intentional manipulation, poor data management and analysis, and inadequate instances of statistical inference. The workshop summarized in this report was designed not to address the social and experimental challenges but instead to focus on the latter issues of improper data management and analysis, inadequate statistical expertise, incomplete data, and difficulties applying sound statistic inference to the available data. Many efforts have emerged over recent years to draw attention to and improve reproducibility of scientific work. This report uniquely focuses on the statistical perspective of three issues: the extent of reproducibility, the causes of reproducibility failures, and the potential remedies for these failures.
Book Synopsis Big Data Meets Survey Science by : Craig A. Hill
Download or read book Big Data Meets Survey Science written by Craig A. Hill and published by John Wiley & Sons. This book was released on 2020-09-29 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.
Download or read book Opening Science written by Sönke Bartling and published by Springer. This book was released on 2013-12-16 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern information and communication technologies, together with a cultural upheaval within the research community, have profoundly changed research in nearly every aspect. Ranging from sharing and discussing ideas in social networks for scientists to new collaborative environments and novel publication formats, knowledge creation and dissemination as we know it is experiencing a vigorous shift towards increased transparency, collaboration and accessibility. Many assume that research workflows will change more in the next 20 years than they have in the last 200. This book provides researchers, decision makers, and other scientific stakeholders with a snapshot of the basics, the tools, and the underlying visions that drive the current scientific (r)evolution, often called ‘Open Science.’
Book Synopsis Reproducibility by : Edo D. Pellizzari
Download or read book Reproducibility written by Edo D. Pellizzari and published by RTI Press. This book was released on 2017 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: Science is allegedly in the midst of a reproducibility crisis, but questions of reproducibility and related principles date back nearly 80 years. Numerous controversies have arisen, especially since 2010, in a wide array of disciplines that stem from the failure to reproduce studies or their findings:biology, biomedical and preclinical research, business and organizational studies, computational sciences, drug discovery, economics, education, epidemiology and statistics, genetics, immunology, policy research, political science, psychology, and sociology. This monograph defines terms and constructs related to reproducible research, weighs key considerations and challenges in reproducing or replicating studies, and discusses transparency in publications that can support reproducible research goals. It attempts to clarify reproducible research, with its attendant (and confusing or even conflicting) lexicon and aims to provide useful background, definitions, and practical guidance for all readers. Among its conclusions: First, researchers must become better educated about these issues, particularly the differences between the concepts and terms. The main benefit is being able to communicate clearly within their own fields and, more importantly, across multiple disciplines. In addition, scientists need to embrace these concepts as part of their responsibilities as good stewards of research funding and as providers of credible information for policy decision making across many areas of public concern. Finally, although focusing on transparency and documentation is essential, ultimately the goal is achieving the most rigorous, high-quality science possible given limitations on time, funding, or other resources. “The authors have written a nuanced and thoughtful primer on scientific reproducibility. By highlighting the social, political, and technical importance of reproducibility, together with a precise description of the related concepts of reproducibility, replicability, and repeatability, this primer provides a significant resource that all practicing researchers should read.” Daniel Reed, Vice President for Research and Economic Development, University of Iowa and former Corporate Vice President, Microsoft “This is a well-written, clearly articulated, and timely primer on the developing and evolving rich terminology of reproducible research. The primer, put together by authors with deep experience and expertise in the topic area, focuses primarily on human-centric research in biomedicine, medicine, and the social sciences as well as reproducibility issues in analytics and computational science. The growing focus on reproducibility will open new vistas in research methodologies, meta analysis, comparative studies of research results, and reuse and adaptation of results from prior research. This primer provides an excellent overview of the subject area, and I would recommend it to anyone interested in coming up to speed on current issues in reproducible research.” Chaitan Baru, Distinguished Scientist and Associate Director for Data Initiatives, San Diego Supercomputing Center; current appointment as Senior Advisor for Data Science, Computer and Information Science and Engineering Directorate, National Science Foundation “Pellizzari et al. have taken on the Herculean task of collecting, synthesizing, and relating the various interpretations of reproducibility used in the research community today, and turned the result into an accessible must-read guide. This important work provides a Rosetta Stone for various stakeholders to discuss and implement solutions that make real progress toward a research enterprise that routinely produces reproducible findings.” Victoria Stodden, Associate Professor at the School of Information Sciences, University of Illinois at Urbana Champaign and co-editor of the books Implementing Reproducible Research and Privacy, Big Data, and the Public Good: Frameworks for Engagement
Download or read book R Markdown written by Yihui Xie and published by CRC Press. This book was released on 2018-07-27 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages. In this book, you will learn Basics: Syntax of Markdown and R code chunks, how to generate figures and tables, and how to use other computing languages Built-in output formats of R Markdown: PDF/HTML/Word/RTF/Markdown documents and ioslides/Slidy/Beamer/PowerPoint presentations Extensions and applications: Dashboards, Tufte handouts, xaringan/reveal.js presentations, websites, books, journal articles, and interactive tutorials Advanced topics: Parameterized reports, HTML widgets, document templates, custom output formats, and Shiny documents. Yihui Xie is a software engineer at RStudio. He has authored and co-authored several R packages, including knitr, rmarkdown, bookdown, blogdown, shiny, xaringan, and animation. He has published three other books, Dynamic Documents with R and knitr, bookdown: Authoring Books and Technical Documents with R Markdown, and blogdown: Creating Websites with R Markdown. J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE. He is an author of several packages in the R Markdown ecosystem including rmarkdown, flexdashboard, learnr, and radix. Garrett Grolemund is the co-author of R for Data Science and author of Hands-On Programming with R. He wrote the lubridate R package and works for RStudio as an advocate who trains engineers to do data science with R and the Tidyverse.
Book Synopsis Data Science in Education Using R by : Ryan A. Estrellado
Download or read book Data Science in Education Using R written by Ryan A. Estrellado and published by Routledge. This book was released on 2020-10-26 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like? If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. The book takes a "learn by doing" approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with. The book finishes with how to get involved in the data science community and how to integrate data science in your education job. This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development.
Book Synopsis Reproducible Research with R and R Studio by : Christopher Gandrud
Download or read book Reproducible Research with R and R Studio written by Christopher Gandrud and published by CRC Press. This book was released on 2018-09-03 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: All the Tools for Gathering and Analyzing Data and Presenting Results Reproducible Research with R and RStudio, Second Edition brings together the skills and tools needed for doing and presenting computational research. Using straightforward examples, the book takes you through an entire reproducible research workflow. This practical workflow enables you to gather and analyze data as well as dynamically present results in print and on the web. New to the Second Edition The rmarkdown package that allows you to create reproducible research documents in PDF, HTML, and Microsoft Word formats using the simple and intuitive Markdown syntax Improvements to RStudio’s interface and capabilities, such as its new tools for handling R Markdown documents Expanded knitr R code chunk capabilities The kable function in the knitr package and the texreg package for dynamically creating tables to present your data and statistical results An improved discussion of file organization, enabling you to take full advantage of relative file paths so that your documents are more easily reproducible across computers and systems The dplyr, magrittr, and tidyr packages for fast data manipulation Numerous modifications to R syntax in user-created packages Changes to GitHub’s and Dropbox’s interfaces Create Dynamic and Highly Reproducible Research This updated book provides all the tools to combine your research with the presentation of your findings. It saves you time searching for information so that you can spend more time actually addressing your research questions. Supplementary files used for the examples and a reproducible research project are available on the author’s website.
Book Synopsis Sharing Publication-Related Data and Materials by : National Research Council
Download or read book Sharing Publication-Related Data and Materials written by National Research Council and published by National Academies Press. This book was released on 2003-04-17 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biologists communicate to the research community and document their scientific accomplishments by publishing in scholarly journals. This report explores the responsibilities of authors to share data, software, and materials related to their publications. In addition to describing the principles that support community standards for sharing different kinds of data and materials, the report makes recommendations for ways to facilitate sharing in the future.
Book Synopsis Reproducibility by : Harald Atmanspacher
Download or read book Reproducibility written by Harald Atmanspacher and published by John Wiley & Sons. This book was released on 2016-07-05 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2017 PROSE Award Honorable Mention The PROSE Awards draw attention to pioneering works of research and for contributions to the conception, production, and design of landmark works in their fields. Featuring peer-reviewed contributions from noted experts in their fields of research, Reproducibility: Principles, Problems, Practices, and Prospects presents state-of-the-art approaches to reproducibility, the gold standard of sound science, from multi- and interdisciplinary perspectives. Including comprehensive coverage for implementing and reflecting the norm of reproducibility in various pertinent fields of research, the book focuses on how the reproducibility of results is applied, how it may be limited, and how such limitations can be understood or even controlled in the natural sciences, computational sciences, life sciences, social sciences, and studies of science and technology. The book presents many chapters devoted to a variety of methods and techniques, as well as their epistemic and ontological underpinnings, which have been developed to safeguard reproducible research and curtail deficits and failures. The book also investigates the political, historical, and social practices that underlie reproducible research in contemporary science studies, including the difficulties of good scientific practice and the ethos of reproducibility in modern innovation societies. Reproducibility: Principles, Problems, Practices, and Prospects is a guide for researchers who are interested in the general and overarching questions behind the concept of reproducibility; for active scientists who are confronted with practical reproducibility problems in their everyday work; and for economic stakeholders and political decision makers who need to better understand the challenges of reproducibility. In addition, the book is a useful in-depth primer for undergraduate and graduate-level courses in scientific methodology and basic issues in the philosophy and sociology of science from a modern perspective. “A comprehensive, insightful treatment of the reproducibility challenges facing science today and of ways in which the scientific community can address them.” Kathleen Hall Jamieson, Elizabeth Ware Packard Professor of Communication, University of Pennsylvania “How can we make sure that reproducible research remains a key imperative of scientific communication under increasing commercialization, media attention, and publication pressure? This handbook offers the first interdisciplinary and fundamental treatment of this important question.”Torsten Hothorn, Professor of Biostatistics, University of Zurich Harald Atmanspacher, PhD, is Associate Fellow and staff member at Collegium Helveticum, ETH and University Zurich and is also President of the Society for Mind-Matter Research. He has pioneered advances in complex dynamical systems research and in a number of topics concerned with the relation between the mental and physical. Sabine Maasen, PhD, is Professor for Sociology of Science and Director of the Munich Center for Technology in Society (TU Munich) and Associate Fellow at Collegium Helveticum (ETH and University Zurich). Her research focuses on the interface of science, technology, and society, notably with respect to neuroscience and its applications.
