Open scientific data : why choosing and reusing the right data matters 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. 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