Representing Scientific Knowledge

The Role of Uncertainty

Authors: Chen, Chaomei, Song, Min

  • Explains the growth of scientific knowledge through diverse theoretical views and data-driven examples
  • Demonstrates the critical and fundamental role of a variety of uncertainties of scientific writing and scientific knowledge
  • Illustrates a solid set of visual analytic and text mining procedures and tools for active researchers
  • Presents a framework of an ambitious research agenda, that may considerably increase the clarity of the status of the state of the art of scientific knowledge
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eBook $69.99
price for Brazil (gross)
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: 1 de Fevereiro de 2018
  • ISBN 978-3-319-62543-0
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover $89.99
price for Brazil
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: 4 de Janeiro de 2018
  • ISBN 978-3-319-62541-6
  • Free shipping for individuals worldwide
About this Textbook

This book is written for anyone who is interested in how a field of research evolves and the fundamental role of understanding uncertainties involved in different levels of analysis, ranging from macroscopic views to meso- and microscopic ones. We introduce a series of computational and visual analytic techniques, from research areas such as text mining, deep learning, information visualization and science mapping, such that readers can apply these tools to the study of a subject matter of their choice. In addition, we set the diverse set of methods in an integrative context, that draws upon insights from philosophical, sociological, and evolutionary theories of what drives the advances of science, such that the readers of the book can guide their own research with their enriched theoretical foundations.

Scientific knowledge is complex. A subject matter is typically built on its own set of concepts, theories, methodologies and findings, discovered by generations of researchers and practitioners.  Scientific knowledge, as known to the scientific community as a whole, experiences constant changes. Some changes are long-lasting, whereas others may be short lived. How can we keep abreast of the state of the art as science advances? How can we effectively and precisely convey the status of the current science to the general public as well as scientists across different disciplines?

The study of scientific knowledge in general has been overwhelmingly focused on scientific knowledge per se. In contrast, the status of scientific knowledge at various levels of granularity has been largely overlooked. This book aims to highlight the role of uncertainties, in developing a better understanding of the status of scientific knowledge at a particular time, and how its status evolves over the course of the development of research. Furthermore, we demonstrate how the knowledge of the types of uncertainties associated with scientific claims serves as an integral and critical part of our domain expertise.

About the authors

Chaomei Chen is a Professor in the College of Computing and Informatics at Drexel University and a Professor in the Department of Library and Information Science at Yonsei University. He is the Editor in Chief of Information Visualization and Chief Specialty Editor of Frontiers in Research Metrics and Analytics. His research interests include mapping scientific frontiers, information visualization, visual analytics, and scientometrics. He has designed and developed the widely used CiteSpace visual analytic tool for analyzing patterns and trends in scientific literature. He is the author of several books such as Mapping Scientific Frontiers (Springer), Turning Points (Springer), and The Fitness of Information (Wiley).

Min Song is an Underwood Distinguished Professor at Yonsei University. He has extensive experience in research and teaching in text mining and big data analytics at both undergraduate and graduate levels. Min has a particular interest in literature-based knowledge discovery in biomedical domains and its extensions to a broader context such as the social media. He is also interested in developing open source text mining software in Java, notably creating the PKDE4J system to support entity and relation extraction for public knowledge discovery.

Buy this book

eBook $69.99
price for Brazil (gross)
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: 1 de Fevereiro de 2018
  • ISBN 978-3-319-62543-0
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover $89.99
price for Brazil
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: 4 de Janeiro de 2018
  • ISBN 978-3-319-62541-6
  • Free shipping for individuals worldwide
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Bibliographic Information

Bibliographic Information
Book Title
Representing Scientific Knowledge
Book Subtitle
The Role of Uncertainty
Authors
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-62543-0
DOI
10.1007/978-3-319-62543-0
Hardcover ISBN
978-3-319-62541-6
Edition Number
1
Number of Pages
XXX, 376
Number of Illustrations and Tables
35 b/w illustrations, 165 illustrations in colour
Topics