Science Dynamics And Research Production
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| Author | : Nikolay K. Vitanov |
| Publisher | : Springer |
| Total Pages | : 299 |
| Release | : 2016-08-01 |
| Genre | : Mathematics |
| ISBN | : 3319416316 |
This book deals with methods to evaluate scientific productivity. In the book statistical methods, deterministic and stochastic models and numerous indexes are discussed that will help the reader to understand the nonlinear science dynamics and to be able to develop or construct systems for appropriate evaluation of research productivity and management of research groups and organizations. The dynamics of science structures and systems is complex, and the evaluation of research productivity requires a combination of qualitative and quantitative methods and measures. The book has three parts. The first part is devoted to mathematical models describing the importance of science for economic growth and systems for the evaluation of research organizations of different size. The second part contains descriptions and discussions of numerous indexes for the evaluation of the productivity of researchers and groups of researchers of different size (up to the comparison of research productivities of research communities of nations). Part three contains discussions of non-Gaussian laws connected to scientific productivity and presents various deterministic and stochastic models of science dynamics and research productivity. The book shows that many famous fat tail distributions as well as many deterministic and stochastic models and processes, which are well known from physics, theory of extreme events or population dynamics, occur also in the description of dynamics of scientific systems and in the description of the characteristics of research productivity. This is not a surprise as scientific systems are nonlinear, open and dissipative.
| Author | : Michael Gibbons |
| Publisher | : SAGE |
| Total Pages | : 196 |
| Release | : 1994-09-09 |
| Genre | : Social Science |
| ISBN | : 9780803977945 |
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
| Author | : Yannis Manolopoulos |
| Publisher | : Springer Nature |
| Total Pages | : 304 |
| Release | : 2021-09-22 |
| Genre | : Computers |
| ISBN | : 3030866688 |
This book provides its readers with an introduction to interesting prediction and science dynamics problems in the field of Science of Science. Prediction focuses on the forecasting of future performance (or impact) of an entity, either a research article or a scientist, and also the prediction of future links in collaboration networks or identifying missing links in citation networks. The single chapters are written in a way that help the reader gain a detailed technical understanding of the corresponding subjects, the strength and weaknesses of the state-of-the-art approaches for each described problem, and the currently open challenges. While chapter 1 provides a useful contribution in the theoretical foundations of the fields of scientometrics and science of science, chapters 2-4 turn the focal point to the study of factors that affect research impact and its dynamics. Chapters 5-7 then focus on article-level measures that quantify the current and future impact of scientific articles. Next, chapters 8-10 investigate subjects relevant to predicting the future impact of individual researchers. Finally, chapters 11-13 focus on science evolution and dynamics, leveraging heterogeneous and interconnected data, where the analysis of research topic trends and their evolution has always played a key role in impact prediction approaches and quantitative analyses in the field of bibliometrics. Each chapter can be read independently, since it includes a detailed description of the problem being investigated along with a thorough discussion and study of the respective state-of-the-art. Due to the cross-disciplinary character of the Science of Science field, the book may be useful to interested readers from a variety of disciplines like information science, information retrieval, network science, informetrics, scientometrics, and machine learning, to name a few. The profiles of the readers may also be diverse ranging from researchers and professors in the respective fields to students and developers being curious about the covered subjects.
| Author | : Andrea Scharnhorst |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 292 |
| Release | : 2012-01-24 |
| Genre | : Social Science |
| ISBN | : 3642230687 |
Models of Science Dynamics aims to capture the structure and evolution of science, the emerging arena in which scholars, science and the communication of science become themselves the basic objects of research. In order to capture the essence of phenomena as diverse as the structure of co-authorship networks or the evolution of citation diffusion patterns, such models can be represented by conceptual models based on historical and ethnographic observations, mathematical descriptions of measurable phenomena, or computational algorithms. Despite its evident importance, the mathematical modeling of science still lacks a unifying framework and a comprehensive study of the topic. This volume fills this gap, reviewing and describing major threads in the mathematical modeling of science dynamics for a wider academic and professional audience. The model classes presented cover stochastic and statistical models, system-dynamics approaches, agent-based simulations, population-dynamics models, and complex-network models. The book comprises an introduction and a foundational chapter that defines and operationalizes terminology used in the study of science, as well as a review chapter that discusses the history of mathematical approaches to modeling science from an algorithmic-historiography perspective. It concludes with a survey of remaining challenges for future science models and their relevance for science and science policy.
| Author | : Michel Callon |
| Publisher | : Springer |
| Total Pages | : 253 |
| Release | : 1986-09-08 |
| Genre | : Social Science |
| ISBN | : 134907408X |
This book is a collection of works regarding the interactions of science, technology, and society.
| Author | : W. Krohn |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 295 |
| Release | : 2012-12-06 |
| Genre | : Science |
| ISBN | : 9400998287 |
The interrelations of science and technology as an object of study seem to have drawn the attention of a number of disciplines: the history of both science and technology, sociology, economics and economic history, and even the philosophy of science. The question that comes to mind is whether the phenomenon itself is new or if advances in the disciplines involved account for this novel interest, or, in fact, if both are intercon nected. When the editors set out to plan this volume, their more or less explicit conviction was that the relationship of science and technology did reveal a new configuration and that the disciplines concerned with 1tS analysis failed at least in part to deal with the change because of conceptual and methodological preconceptions. To say this does not imply a verdict on the insufficiency of one and the superiority of any other one disciplinary approach. Rather, the situation is much more complex. In economics, for example, the interest in the relationship between science and technology is deeply influenced by the theoretical problem of accounting for the factors of economic growth. The primary concern is with technology and the problem is whether the market induces technological advances or whether they induce new demands that explain the subsequent diffusion of new technologies. Science is generally considered to be an exogenous factor not directly subject to market forces and, therefore, appears to be of no interest.
| Author | : Wilfried Ehlers |
| Publisher | : Cabi |
| Total Pages | : 0 |
| Release | : 2016 |
| Genre | : Technology & Engineering |
| ISBN | : 9781780643823 |
"Meagre water supply causes severe problems in the growth of plants, which rely on sufficient water transmitted by the soil to meet their needs. This new edition of Water Dynamics in Plant Production describes the basic scientific principles of water transport in the soil-plant-atmosphere continuum, explains the linkage between transpirational water use and dry matter production paying particular attention to the various agronomic strategies for adaptation to climate-driven limitations of water resources"--Publisher's website.
| Author | : Carl M. Cohen |
| Publisher | : CSHL Press |
| Total Pages | : 184 |
| Release | : 2005 |
| Genre | : Comportement organisationnel |
| ISBN | : 0879698160 |
"Lab Dynamics is a book about the challenges to doing science and dealing with the individuals involved, including oneself. The authors, a scientist and a psychotherapist, draw on principles of group and behavioral psychology but speak to scientists in their own language about their own experiences. They offer in-depth, practical advice, real-life examples, and exercises tailored to scientific and technical workplaces on topics as diverse as conflict resolution, negotiation, dealing with supervision, working with competing peers, and making the transition from academia to industry." "This is a uniquely valuable contribution to the scientific literature, on a subject of direct importance to lab heads, postdocs, and students. It is also required reading for senior staff concerned about improving efficiency and effectiveness in academic and industrial research."--BOOK JACKET
| Author | : Daniel Kaplan |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 438 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461208238 |
Mathematics is playing an ever more important role in the physical and biological sciences, provoking a blurring of boundaries between scientific disciplines and a resurgence of interest in the modern as well as the classical techniques of applied mathematics. This renewal of interest, both in research and teaching, has led to the establishment of the series: Texts in Applied Mathematics ( TAM). The development of new courses is a natural consequence of a high level of excitement on the research frontier as newer techniques, such as numerical and symbolic computer systems, dynamical systems, and chaos, mix with and reinforce the traditional methods of applied mathematics. Thus, the purpose of this textbook series is to meet the current and future needs of these advances and encourage the teaching of new courses. TAM will publish textbooks suitable for use in advanced undergraduate and beginning graduate courses, and will complement the Applied Mathematical Sciences (AMS) series, which will focus on advanced textbooks and research level monographs. About the Authors Daniel Kaplan specializes in the analysis of data using techniques motivated by nonlinear dynamics. His primary interest is in the interpretation of irregular physiological rhythms, but the methods he has developed have been used in geo physics, economics, marine ecology, and other fields. He joined McGill in 1991, after receiving his Ph.D from Harvard University and working at MIT. His un dergraduate studies were completed at Swarthmore College. He has worked with several instrumentation companies to develop novel types of medical monitors.
| Author | : Steven L. Brunton |
| Publisher | : Cambridge University Press |
| Total Pages | : 615 |
| Release | : 2022-05-05 |
| Genre | : Computers |
| ISBN | : 1009098489 |
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
