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Academic Press Classification Made Relevant: How Scientists Build and Use Classifications and Ontologies

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Description

Classification Made Relevant explains how classifications and ontologies are designed, and how they are used to analyze scientific information. It is through our description of the relationships among classes of objects that we are able to simplify knowledge and explore the ways in which individual classified objects behave. The book begins by describing the fundamentals of classification and leads up to a description of how computer scientists use object-oriented programming languages to model classifications and ontologies. Numerous examples are chosen from the Classification of Life, the Periodic Table of the Elements, and the symmetry relationships contained within the Classification Theorem of Finite Simple Groups. When these three classifications are tied together, they provide a relational hierarchy connecting all of the natural sciences. This book is intended to reach a multidisciplinary audience of students and professionals working in the data sciences, the library sciences, and all of the STEM sciences. The chapters introduce and describe general concepts that can be understood by any intelligent reader. With each new concept, there follow practical examples selected from various scientific disciplines. In these cases, technical points and specialized vocabulary are linked to glossary items, where the item is clarified and expanded. Technical terms in the data sciences often have different meanings, depending on the reader's specific discipline. The word “ontology has so many meanings, it has become meaningless. Skeptics can google on the word “ontology to quickly confirm the inchoate status of this subject. In such cases, the glossary describes the different way the term has been used and will clarify its meaning within the book's context. For the benefit of computer scientists, the glossary contains short scripts written in Perl or Python or Ruby. Non-programmers will be spared from reading computer code, without missing out on the concepts covered in each chapter. By using the glossary links, every reader experiences a version of this book tailored to their personal needs and preferences. Review "One of the ways in which human beings attempt to understand relationships among objects, beings and concepts is through the process of classification. Sometimes our classifications are simple (heavy vs light) and sometimes complex (the phylogeny of living things), but each attempt to develop a classification system represents an attempt to improve our understanding of the world around us. In this tour de force, Dr. Berman creates a unifying framework by which to understand successful (and unsuccessful) classification systems in fields ranging from mathematics to biology, showing the dependence of all successful classifications to at least implicit incorporation/acceptance of previous classifications in the mathematics – physics – chemistry – biology chain, and without losing sight of the fact that the purpose of classification is understanding. Thus, development of classification systems both complements and frames the appropriate use of other tools, based on probabilistic and continuous mathematics, for understanding the world around us. The clear and detailed expositions that Dr. Berman provides in this book are useful to both scientists who wish to develop a deeper understanding of how concepts like that of the periodic table both encapsulate known science and guide its further development, and to non-scientists who wish to develop a better understanding of how scientists think. I highly recommend it." --Timothy J. O'Leary, MD, PhD, Adjunct Professor of Pathology, University of Maryland School of Medicine, Baltimore, MD, United States; former Chief Research and Development Officer, Department of Veterans Affairs Review Investigates how classifications and ontologies are used to analyze scientific information From the Back Cover <p>"One of the ways in whic

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
01 February 2022
Listed Since
04 October 2021

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