Representing Scientific Knowledge

Autor: Chaomei Chen, Min Song

Limbă:

Legare: Copertă tare

Editura: Springer International Publishing AG

Disponibilitate: În depozitul extern

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This book is written for anyone who is interested in how a field of research evolves and the fundame...

Informații despre carte

Autor

Chaomei Chen, Min Song

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2018

Pagini

375

EAN

9783319625416

ISBN

9783319625416

Enbook ID

16475204

Editura

Springer International Publishing AG

Greutate

766

Dimensiuni

241 x 161 x 33

Descriere completă

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.

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