The Fitness of Information: Quantitative Assessments of Critical Evidence

Theories and practices to assess critical information in a complex adaptive system Organized for readers to follow along easily, The Fitness of Information: Quantitative Assessments of Critical Evidence provides a structured outline of the key challenges in assessing crucial information in a complex adaptive system. Illustrating a variety of computational and explanatory challenges, the book demonstrates principles and practical implications of exploring and assessing the fitness of information in an extensible framework of adaptive landscapes.  The book’s first three chapters introduce fundamental principles and practical examples in connection to the nature of aesthetics, mental models, and the subjectivity of evidence. In particular, the underlying question is how these issues can be addressed quantitatively, not only computationally but also explanatorily. The next chapter illustrates how one can reduce the level of complexity in understanding the structure and dynamics of scientific knowledge through the design and use of the CiteSpace system for visualizing and analyzing emerging trends in scientific literature. The following two chapters explain the concepts of structural variation and the fitness of information in a framework that builds on the idea of fitness landscape originally introduced to study population evolution. The final chapter presents a dual–map overlay technique and demonstrates how it supports a variety of analytic tasks for a new type of portfolio analysis.   The Fitness of Information: Quantitative Assessments of Critical Evidence also features: In–depth case studies and examples that characterizes far–reaching concepts, illustrates underlying principles and demonstrates profound challenges at various levels of analytic reasoning   Wide–ranging topics that underline the common theme, from the subjectivity of evidence in criminal trials to detecting early signs of critical transitions and mechanisms behind radical patents An extensible and unifying framework for visual analytics by transforming analytic reasoning tasks to the assessment of critical evidence   The Fitness of Information: Quantitative Assessments of Critical Evidence is a suitable reference for researchers, analysts, and practitioners who are interested in analyzing evidence and making decisions with incomplete, uncertain, and even conflicting information. The book is also an excellent textbook for upper–undergraduate and graduate–level courses on visual analytics, information visualization, and business analytics and decision support systems.

Chapter 1 Attention and Aesthetics 8 1.1 Attention 8 1.2 Gestalt Principles 11 1.3 Aesthetics 16 1.4 The Index of the Interesting 21 1.5 Summary 26 Bibliography 27 Chapter 2 Mental Models 29 2.1 Mental Models 29 2.2 Creativity 44 2.3 Foresights 53 2.4 Summary 57 Bibliography 57 Chapter 3 Subjectivity of Evidence 61 3.1 The Value of Information 61 3.2 Causes Célèbre 63 3.3 The Da Vinci Code 74 3.4 Supreme Court Opinions 79 3.5 Apple versus Samsung 82 3.6 Summary 83 Bibliography 84 Chapter 4 Visualizing the Growth of Knowledge 86 4.1 Progressive Knowledge Domain Visualization 86 4.2 CiteSpace 96 4.3 Examples 109 4.4 Summary 119 Bibliography 119 Chapter 5 Fitness Landscapes 122 5.1 Cognitive Maps 122 5.2 Fitness Landscapes 124 5.3 Applications of Fitness Landscapes 131 5.4 Summary 140 Bibliography 140 Chapter 6 Structural Variation 141 6.1 Complex Adaptive Systems 141 6.2 Radical Patents 147 6.3 Bridging the Gaps 155 6.4 Applications 161 6.5 Summary 172 Bibliography 173 Chapter 7 Gap Analytics 177 7.1 Portfolio Analysis and Risk Assessment 178 7.2 Interactive Overlays 183 7.3 Examples of Dual–Map Overlays 189 7.4 Summary 202 7.5 Conclusion 203 Bibliography 205

Chaomei Chen, PhD, is a Professor of Informatics in the College of Computing and Informatics at Drexel University. He is the creator of the widely used software CiteSpace and author of several other books. Dr. Chen’s research expertise includes information visualization, visual analytics, quantitative studies of scientific literature, and theories of scientific discoveries.