Representing Scientific Knowledge

The Role of Uncertainty

  • Chaomei Chen
  • Min Song

Table of contents

  1. Front Matter
    Pages i-xxxii
  2. Chaomei Chen, Min Song
    Pages 37-55
  3. Chaomei Chen, Min Song
    Pages 57-137
  4. Chaomei Chen, Min Song
    Pages 139-204
  5. Chaomei Chen, Min Song
    Pages 205-221
  6. Chaomei Chen, Min Song
    Pages 223-261
  7. Chaomei Chen, Min Song
    Pages 263-281
  8. Chaomei Chen, Min Song
    Pages 283-336
  9. Chaomei Chen, Min Song
    Pages 337-375

About this book


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 various stages of the development of a scientific domain. In a nutshell, the uncertainty of scientific knowledge is how much we really know what we think we know. We introduce a series of computational and visual analytic techniques from research areas such as science mapping, text mining, literature-based discovery, and semantic network analysis so 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 so 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 changes constantly. Some changes are profound and long-lasting, whereas others may be transient. How can we keep abreast of the state of the art as science advances? How can we effectively and precisely capture the epistemic status of the current science?

The study of scientific knowledge in general has been overwhelmingly focusing on scientific knowledge per se. In contrast, the epistemic status of scientific knowledge at various levels of granularity has been largely overlooked, especially when the focus is on the development of a scientific domain. 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.


Knowledge Domain Visualization Knowledge Extraction Science Mapping Visual Perception Visualization

Authors and affiliations

  • Chaomei Chen
    • 1
  • Min Song
    • 2
  1. 1.College of Computing and InformaticsDrexel UniversityPhiladelphiaUSA
  2. 2.Department of Library and Information ScienceYonsei UniversitySeoulKorea (Republic of)

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-62541-6
  • Online ISBN 978-3-319-62543-0
  • Buy this book on publisher's site
Industry Sectors
Finance, Business & Banking
IT & Software
Consumer Packaged Goods
Energy, Utilities & Environment