As branches of research and knowledge continue to expand, platforms for gathering and understanding new information become important aspects of organizational improvement. Contemporary Knowledge and Systems Science provides emerging research on the methods and applications of knowledge systems in social science, economics, and technological developments. While highlighting topics such as knowledge retention, organizational information, and evolutionary algorithms, this publication explores the different types of new knowledge from a systems perspective. This book is an important resource for researchers, academics, practitioners, and graduate-level students seeking current research on the connections between technology and information in order to manage new data.
As branches of research and knowledge continue to expand, platforms for gathering and understanding new information become important aspects of organizational improvement. Contemporary Knowledge and Systems Science provides emerging research on the methods and applications of knowledge systems in social science, economics, and technological developments. While highlighting topics such as knowledge retention, organizational information, and evolutionary algorithms, this publication explores the different types of new knowledge from a systems perspective. This book is an important resource for researchers, academics, practitioners, and graduate-level students seeking current research on the connections between technology and information in order to manage new data.
In this provocative and broad-ranging work, the authors argue that the ways in which knowledge - scientific, social and cultural - is produced are undergoing fundamental changes at the end of the twentieth century. They claim that these changes mark a distinct shift into a new mode of knowledge production which is replacing or reforming established institutions, disciplines, practices and policies. Identifying features of the new mode of knowledge production - reflexivity, transdisciplinarity, heterogeneity - the authors show how these features connect with the changing role of knowledge in social relations. While the knowledge produced by research and development in science and technology is accorded central concern, the
The role that “system” has played in the shaping and reshaping of modern knowledge, from Galileo and Newton to our own “computational universe.” A system can describe what we see (the solar system), operate a computer (Windows 10), or be made on a page (the fourteen engineered lines of a sonnet). In this book, Clifford Siskin shows that system is best understood as a genre—a form that works physically in the world to mediate our efforts to understand it. Indeed, many Enlightenment authors published works they called “system” to compete with the essay and the treatise. Drawing on the history of system from Galileo's “message from the stars” and Newton's “system of the world” to today's “computational universe,” Siskin illuminates the role that the genre of system has played in the shaping and reshaping of modern knowledge. Previous engagements with systems have involved making them, using them, or imagining better ones. Siskin offers an innovative perspective by investigating system itself. He considers the past and present, moving from the “system of the world” to “a world full of systems.” He traces the turn to system in the seventeenth and eighteenth centuries, and describes this primary form of Enlightenment as a mediator of political, cultural, and social modernity—pointing to the moment when people began to “blame the system” for working both too well (“you can't beat the system”) and not well enough (it always seems to “break down”). Throughout, his touchstones are: what system is and how it has changed; how it has mediated knowledge; and how it has worked in the world.
Various systems science and engineering disciplines are covered and challenging new research issues in these disciplines are revealed. They will be extremely valuable for the readers to search for some new research directions and problems. Chapters are contributed by world-renowned systems engineers Chapters include discussions and conclusions Readers can grasp each event holistically without having professional expertise in the field
Within the past ten years, tremendous innovations have been brought forth in information technology and knowledge management. Some of the key technical innovations have included the introduction of social media, artificial intelligence, as well as improved network connectivity and capacity. Effective Knowledge Management Systems in Modern Society is a critical scholarly resource that presents an overview of how technical, social, and process changes are impacting the way knowledge systems are being designed. Featuring coverage on a broad range of topics such as knowledge engineering, cognitive ergonomics, and interorganizational knowledge, this book is geared toward consultants, practitioners, and researchers seeking current research on how new approaches in knowledge management impact information technology professionals.
This book provides readers the idea of systemically synthesizing various kind of knowledge, which needs to combine analytical thinking and synthetic thinking. Systems science is expected to help in solving contemporary complex problems, utilizing interdisciplinary knowledge effectively and combining analytical thinking and synthetic thinking efficiently. However, traditional systems science has been divided into two schools: one seeks a systematic procedure to give a correct objective answer; the other develops an emergent, systemic process so that the user can continue exploratory learning. It is not an exaggeration to say that analytical thinking and synthetic thinking have been developed independently, in different schools. This book integrates approaches developed in these two schools, using ideas in knowledge science that have been emerging recently under the influence of Eastern thinking. It emphasizes the importance of utilizing intuition in systems approaches, whereas other books usually try to solve problems rationally and objectively, rejecting subjectivity. This book never denies rationality and objectivity; however, complex problems of today do not always yield to complete analysis. The novelty of this present volume is that it takes in the ideas of synthetic thinking in knowledge science to develop systems science further. The chapter contributors, who are experienced systems scientists with a profound understanding of knowledge management, discuss knowledge synthesis from the Western and Eastern cultural perspectives. The book introduces a theory on systemic knowledge synthesis in an odd chapter and then presents an application of the theory in the next chapter in order to contribute to developing translational systems science.
What Is Scientific Knowledge? is a much-needed collection of introductory-level chapters on the epistemology of science. Renowned historians, philosophers, science educators, and cognitive scientists have authored 19 original contributions specifically for this volume. The chapters, accessible for students in both philosophy and the sciences, serve as helpful introductions to the primary debates surrounding scientific knowledge. First-year undergraduates can readily understand the variety of discussions in the volume, and yet advanced students and scholars will encounter chapters rich enough to engage their many interests. The variety and coverage in this volume make it the perfect choice for the primary text in courses on scientific knowledge. It can also be used as a supplemental book in classes in epistemology, philosophy of science, and other related areas. Key features: * an accessible and comprehensive introduction to the epistemology of science for a wide variety of students (both undergraduate- and graduate-level) and researchers * written by an international team of senior researchers and the most promising junior scholars * addresses several questions that students and lay people interested in science may already have, including questions about how scientific knowledge is gained, its nature, and the challenges it faces.
“The Knowledge Machine is the most stunningly illuminating book of the last several decades regarding the all-important scientific enterprise.” —Rebecca Newberger Goldstein, author of Plato at the Googleplex A paradigm-shifting work, The Knowledge Machine revolutionizes our understanding of the origins and structure of science. • Why is science so powerful? • Why did it take so long—two thousand years after the invention of philosophy and mathematics—for the human race to start using science to learn the secrets of the universe? In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument. Like such classic works as Karl Popper’s The Logic of Scientific Discovery and Thomas Kuhn’s The Structure of Scientific Revolutions, The Knowledge Machine grapples with the meaning and origins of science, using a plethora of vivid historical examples to demonstrate that scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens calls this scientific code the iron rule of explanation, and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “With a mixture of philosophical and historical argument, and written in an engrossing style” (Alan Ryan), The Knowledge Machine provides captivating portraits of some of the greatest luminaries in science’s history, including Isaac Newton, the chief architect of modern science and its foundational theories of motion and gravitation; William Whewell, perhaps the greatest philosopher-scientist of the early nineteenth century; and Murray Gell-Mann, discoverer of the quark. Today, Strevens argues, in the face of threats from a changing climate and global pandemics, the idiosyncratic but highly effective scientific knowledge machine must be protected from politicians, commercial interests, and even scientists themselves who seek to open it up, to make it less narrow and more rational—and thus to undermine its devotedly empirical search for truth. Rich with illuminating and often delightfully quirky illustrations, The Knowledge Machine, written in a winningly accessible style that belies the import of its revisionist and groundbreaking concepts, radically reframes much of what we thought we knew about the origins of the modern world.
This book discusses technology and systems to create valuable ideas from data through the construction of knowledge. The primary concern is to make better decisions about economic and management issues in today’s information-flooded society. Human creative activity is in the realm of soft technology, with no physical entity to operate. Focusing on the ability of knowledge as judgment power, this definition results: “Knowledge technology is soft technology that underpins the human creative activities of converting data and information into knowledge, creating new ideas based on that knowledge and validating those ideas.” That definition includes a wide range of soft technologies developed in informatics, management studies, and systems science. The knowledge system creates ideas from data and knowledge through knowledge technologies. Based on the proposition that knowledge emerges by the interaction between explicit and tacit knowledge, another definition is possible: “The knowledge system is a system that promotes interaction between codified and personalized knowledge and creates ideas for solving a specific problem.” Codified knowledge includes data and information, while personalized knowledge is empirical knowledge or wisdom that is difficult to put into words. Building a knowledge system requires mathematical or intelligent knowledge technology and participatory knowledge technology to create or manage codified knowledge and personalized knowledge. For example, a company builds cross-sectional knowledge systems by gathering human resources from various departments, according to the purpose, as in new product development or sales promotion. Chapter 1 defines knowledge technology and the knowledge system and organizes the challenges in their development, while Chapters 2 through 9 introduce mathematical or intelligent knowledge technologies by researchers at the forefront of knowledge technology development.
