Preserving Scientific Data on Our Physical Universe
Preserving Scientific Data on Our Physical Universe

Author: National Research Council

Publisher: National Academies Press

Published: 1995-04-19

Total Pages: 80

ISBN-13: 0309176638

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This book advises the National Archives and Records Administration and federal R&D agencies on the long-term retention of scientific and technical data, particularly in electronic formats. It proposes the creation of a National Scientific Information Resource Federation, which would apply a strategic data life-cycle management plan to better link the government's existing scientific data holdings and improve public access to those holdings. The book is expected to draw attention to data management concerns in the context of the current government emphasis on promoting a National Information Infrastructure and to make a significant contribution to improving the inadequate situation regarding our nation's valuable scientific data and information resources.

Scientific Data Management
Scientific Data Management

Author: Arie Shoshani

Publisher: CRC Press

Published: 2009-12-16

Total Pages: 592

ISBN-13: 1420069810

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Dealing with the volume, complexity, and diversity of data currently being generated by scientific experiments and simulations often causes scientists to waste productive time. Scientific Data Management: Challenges, Technology, and Deployment describes cutting-edge technologies and solutions for managing and analyzing vast amounts of data, helping

Data Science
Data Science

Author: John D. Kelleher

Publisher: MIT Press

Published: 2018-04-13

Total Pages: 282

ISBN-13: 0262347032

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A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges. The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges. It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.