杭州电子科技大学图书馆书目检索系统

Online Public Access Catalogue

题名/责任者:

Open scientific data : why choosing and reusing the right data matters / edited by Vera J. Lipton

出版发行项:

London : IntechOpen, 2020

ISBN:

9781838809843:

ISBN:

1838809848

载体形态项:

230 pages : illustrations (some color) ; 22 cm

个人责任者:

Lipton, Vera J., author.

附加团体名称:

Ohio Library and Information Network.

论题主题:

Big data.

论题主题:

Research-Data processing.

论题主题:

Science-Data processing.

论题主题:

Data mining.

论题主题:

Open access publishing.

中图法分类号:

TP274

书目附注:

Includes bibliographical references.

内容附注:

Foreword / Marco Ricolfi -- Abstract -- Introduction: opening up data in scientific research -- The case for open scientific data: theory, benefits, costs and opportunities -- The current policies of research funders and publishers -- The unclear meaning of open scientific data -- Research data management at CERN -- Open sharing of clinical trial data -- Legal issues arising in open scientific data -- The staged model for open scientific data -- Conclusion: towards achievable and sustainable open scientific data.

摘要附注:

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.

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