Research Data and Reproducibility

The Data Book: Collection and Management of Research Data is the first practical book written for researchers and research team members covering how to collect and manage data for research. The book covers basic types of data and fundamentals of how data grow, move and change over time. Focusing on pre-publication data collection and handling, the text illustrates use of these key concepts to match data collection and management methods to a particular study, in essence, making good decisions about data. The first section of the book defines data, introduces fundamental types of data that bear on methodology to collect and manage them, and covers data management planning and research reproducibility. The second section covers basic principles of and options for data collection and processing emphasizing error resistance and traceability. The third section focuses on managing the data collection and processing stages of research such that quality is consistent and ultimately capable of supporting conclusions drawn from data. The final section of the book covers principles of data security, sharing, and archival. This book will help graduate students and researchers systematically identify and implement appropriate data collection and handling methods.

Data Stewardship for Open Science: Implementing FAIR Principles has been written with the intention of making scientists, funders, and innovators in all disciplines and stages of their professional activities broadly aware of the need, complexity, and challenges associated with open science, modern science communication, and data stewardship. The FAIR principles are used as a guide throughout the text, and this book should leave experimentalists consciously incompetent about data stewardship and motivated to respect data stewards as representatives of a new profession, while possibly motivating others to consider a career in the field. The ebook, avalable for no additional cost when you buy the paperback, will be updated every 6 months on average (providing that significant updates are needed or avaialble). Readers will have the opportunity to contribute material towards these updates, and to develop their own data management plans, via the free Data Stewardship Wizard.

Research Data Management (RDM) has become a professional topic of great importance internationally following changes in scholarship and government policies about the sharing of research data. Exploring Research Data Management provides an accessible introduction and guide to RDM with engaging tasks for the reader to follow and develop their knowledge. Starting by exploring the world of research and the importance and complexity of data in the research process, the book considers how a multi-professional support service can be created then examines the decisions that need to be made in designing different types of research data service from local policy creation, training, through to creating a data repository.

Research funders in the UK, USA and across Europe are implementing data management and sharing policies to maximize openness of data, transparency and accountability of the research they support. Written by experts from the UK Data Archive with over 20 years experience, this book gives post-graduate students, researchers and research support staff the data management skills required in today's changing research environment. The book features guidance on: how to plan your research using a data management checklist how to format and organize data how to store and transfer data research ethics and privacy in data sharing and intellectual property rights data strategies for collaborative research how to publish and cite data how to make use of other people's research data, illustrated with six real-life case studies of data use.  

In the behavioral sciences today, there is increasing emphasis on transparency, and the need for research studies to be made replicable. This book presents a straightforward approach to managing and documenting one's data so that other researchers can repeat the study. While data management may seem intimidating to new researchers, this book shows how easy it can (and should!) be. The first chapter presents a basic structure of folders and subfolders for organizing data files, and then each subsequent chapter delves into details for a specific folder. Step by step, readers learn to label and archive different kinds of project documents and data files, including original, processed, and working data. Readers also learn to write command codes showing exactly how the original data are analyzed. Examples illustrate how to document the most common types of research (an online survey, a paper questionnaire, and a multiple-trial experiment). Since major research funders now require recipients to meet strict standards for data handling, this book will foster a vital career skill for students and promote transparency and replicability of research.

Innovative technologies are changing the way research is performed, preserved, and communicated. Managing Scientific Information and Research Data explores how these technologies are used and provides detailed analysis of the approaches and tools developed to manage scientific information and data. Following an introduction, the book is then divided into 15 chapters discussing the changes in scientific communication; new models of publishing and peer review; ethics in scientific communication; preservation of data; discovery tools; discipline-specific practices of researchers for gathering and using scientific information; academic social networks; bibliographic management tools; information literacy and the information needs of students and researchers; the involvement of academic libraries in eScience and the new opportunities it presents to librarians; and interviews with experts in scientific information and publishing. Promotes innovative technologies for creating, sharing and managing scientific content Presents new models of scientific publishing, peer review, and dissemination of information Serves as a practical guide for researchers, students, and librarians on how to discover, filter, and manage scientific information Advocates for the adoption of unique author identifiers such as ORCID and ResearcherID Looks into new tools that make scientific information easy to discover and manage Shows what eScience is and why it is becoming a priority for academic libraries Demonstrates how Electronic Laboratory Notebooks can be used to record, store, share, and manage research data Shows how social media and the new area of Altmetrics increase researchers' visibility and measure attention to their research Directs to sources for datasets Provides directions on choosing and using bibliographic management tools Critically examines the metrics used to evaluate research impact Aids strategic thinking and informs decision making

This book opens discussion on the topics of data management. It is not a new topic at all because scientists deal with data every day; what makes this topic unique is the scale of data everyone is dealing with nowadays and the support that it needs. It is no longer an individual initiative but a common interest and collaborative effort for everyone involved in the life cycle of data, information, and knowledge, who might be researchers, librarians/information specialists, policy makers, or administrators. This book originated from the American Chemical Society (ACS) National Meeting Chemical Information Division (CINF) Symposium entitled "Data Archiving, E-Science and Primary Data" in Anaheim, California on March 28, 2011. It was organized to "explore the challenges and opportunities of supporting e-science research and data management in research libraries" with particular interest in "current applications and practices and preparation opportunities for information professionals". Only one author from the original symposium was able to contribute. With this interesting twist, the book now brings new and refreshing perspectives to the topic by authors from different sectors with diverse background and experience; researchers in science, information science and data management, librarians, and publishers.

Biomedical research results in the collection and storage of increasingly large and complex data sets. Preserving those data so that they are discoverable, accessible, and interpretable accelerates scientific discovery and improves health outcomes, but requires that researchers, data curators, and data archivists consider the long-term disposition of data and the costs of preserving, archiving, and promoting access to them. Life Cycle Decisions for Biomedical Data examines and assesses approaches and considerations for forecasting costs for preserving, archiving, and promoting access to biomedical research data. This report provides a comprehensive conceptual framework for cost-effective decision making that encourages data accessibility and reuse for researchers, data managers, data archivists, data scientists, and institutions that support platforms that enable biomedical research data preservation, discoverability, and use.

As platforms for sharing, re-using and storing data, research data repositories are integral to open science policy. This book provides a comprehensive approach to these data repositories, their functionalities, uses, issues and prospects. Taking France as an example, the current landscape of data repositories is considered, including discussion of the idea of a national repository and a comparative study of several national systems. The international re3data directory is outlined and a collection of six case studies of model repositories, both public and private, are detailed (CDS, Data INRAE, SEANOE, Nakala, Figshare and Data Mendeley). Research Data Sharing and Valorization also includes appendices containing a number of websites and reference texts from the French Ministry of Higher Education, Research and Innovation, and the CNRS. To the authors' knowledge, it is the first book to be entirely devoted to these new platforms and is aimed at researchers, teachers, students and professionals working with scientific and technical data and information.