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Author: Vera Lipton
Publisher: BoD – Books on Demand
ISBN: 1838809848
Category : Computers
Languages : en
Pages : 232
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Book Description
This book shows how the vision for open access to scientific data can be more readily achieved through a staged model that research funders, policy makers, scientists, and research organizations can adopt in their practice. Drawing on her own experiences with data processing, on early findings with open scientific data at CERN (the European Organization for Nuclear Research), and from case studies of shared clinical trial data, the author updates our understanding of research data - what it is; how it dynamically evolves across different scientific disciplines and across various stages of research practice; and how it can, and indeed should, be shared at any of those stages. The result is a flexible and pragmatic path for implementing open scientific data.
Author: Vera Lipton
Publisher: BoD – Books on Demand
ISBN: 1838809848
Category : Computers
Languages : en
Pages : 232
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Book Description
This book shows how the vision for open access to scientific data can be more readily achieved through a staged model that research funders, policy makers, scientists, and research organizations can adopt in their practice. Drawing on her own experiences with data processing, on early findings with open scientific data at CERN (the European Organization for Nuclear Research), and from case studies of shared clinical trial data, the author updates our understanding of research data - what it is; how it dynamically evolves across different scientific disciplines and across various stages of research practice; and how it can, and indeed should, be shared at any of those stages. The result is a flexible and pragmatic path for implementing open scientific data.
Author: Sönke Bartling
Publisher: Springer
ISBN: 3319000268
Category : Science
Languages : en
Pages : 339
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Book Description
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.’
Author: National Research Council (U.S.)
Publisher: National Academies
ISBN:
Category : Communication in science
Languages : en
Pages : 50
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Book Description
Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
ISBN: 1491910364
Category : Computers
Languages : en
Pages : 521
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Book Description
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Author: Svetla Baykoucheva
Publisher: Chandos Publishing
ISBN: 0081002378
Category : Business & Economics
Languages : en
Pages : 162
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Book Description
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
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309167086
Category : Science
Languages : en
Pages : 238
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Book Description
This symposium brought together leading experts and managers from the public and private sectors who are involved in the creation, dissemination, and use of scientific and technical data and information (STI) to: (1) describe and discuss the role and the benefits and costsâ€"both economic and otherâ€"of the public domain in STI in the research and education context, (2) to identify and analyze the legal, economic, and technological pressures on the public domain in STI in research and education, (3) describe and discuss existing and proposed approaches to preserving the public domain in STI in the United States, and (4) identify issues that may require further analysis.
Author: Susanne Hecker
Publisher: UCL Press
ISBN: 1787352331
Category : Science
Languages : en
Pages : 582
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Book Description
Citizen science, the active participation of the public in scientific research projects, is a rapidly expanding field in open science and open innovation. It provides an integrated model of public knowledge production and engagement with science. As a growing worldwide phenomenon, it is invigorated by evolving new technologies that connect people easily and effectively with the scientific community. Catalysed by citizens’ wishes to be actively involved in scientific processes, as a result of recent societal trends, it also offers contributions to the rise in tertiary education. In addition, citizen science provides a valuable tool for citizens to play a more active role in sustainable development. This book identifies and explains the role of citizen science within innovation in science and society, and as a vibrant and productive science-policy interface. The scope of this volume is global, geared towards identifying solutions and lessons to be applied across science, practice and policy. The chapters consider the role of citizen science in the context of the wider agenda of open science and open innovation, and discuss progress towards responsible research and innovation, two of the most critical aspects of science today.
Author: Vera J. Lipton
Publisher:
ISBN: 9781838809850
Category : Big data
Languages : en
Pages :
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Book Description
Public science is critical to the economy and to society. However, much of the beneficial impact of scientific research only occurs when scientific knowledge is disseminated broadly and is used by others. This book examines the emerging policy, law and practice of facilitating open access to scientific research data. One particular focus is to examine the open data policies recently introduced by research funders and publishers, and the potential in these for driving the practice of open scientific data into the future. This study identifies five major stumbling blocks to sustainable open scientific data. Firstly, it is the prevailing mindset that facilitating open access to data is analogous to facilitating open access to publications and, therefore, research data can easily be shared, with research funders and librarians effectively leading the process. Secondly, it is the unclear meaning of the term data which causes confusion among stakeholders. Thirdly, it is the misunderstood incentives for data sharing and the additional inputs required from researchers. Fourthly, data privacy—an issue that only applies to selected research datasets, and yet appears to dominate the discussion about open research data. Finally, there is a copyright law, which poses challenges at different stages of data release and reuse. In this book, it is argued that the above problems can be addressed using a staged model for open scientific data. I draw specifically on the practice with open scientific data at CERN (the European Organization for Nuclear Research) and the practice of sharing clinical trial data to argue that open data can be shared at various stages of processing and diversification. This model is supplemented by recommendations proposing changes to existing open data mandates and the introduction of a text and data mining exemption into Australian copyright law.
Author: Daniel Burgos
Publisher: Springer Nature
ISBN: 9811542767
Category : Education
Languages : en
Pages : 199
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Book Description
This open access book presents how Open Science is a powerful tool to boost Higher Education. The book introduces the reader into Open Access, Open Technology, Open Data, Open Research results, Open Licensing, Open Accreditation, Open Certification, Open Policy and, of course, Open Educational Resources. It brings all these key topics from major players in the field; experts that present the current state of the art and the forthcoming steps towards a useful and effective implementation. This book presents radical, transgenic solutions for recurrent and long-standing problems in Higher Education. Every chapter presents a clear view and a related solution to make Higher Education progress and implement tools and strategies to improve the user’s performance and learning experience. This book is part of a trilogy with companion volumes on Radical Solutions & Learning Analytics and Radical Solutions & eLearning.
Author: Catherine D'Ignazio
Publisher: MIT Press
ISBN: 026254718X
Category : Social Science
Languages : en
Pages : 328
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Book Description
A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.
