Models of Science Dynamics: Encounters Between Complexity Theory and Information Sciences - Couverture rigide
Synopsis
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.
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Présentation de l'éditeur
This volume explores the structure and evolution of science, an emerging field where scholars, science and science communication themselves become the basic objects of research. It aims to provide, for the first time, a unified mathematical model of science.
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Models of Science Dynamics (eng)
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Models of Science Dynamics: Encounters Between Complexity Theory and Information Sciences (Springer Complexity: Understanding Complex Systems)
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Springer-Verlag Publishing, 2012
ISBN 10 : 3642230679
ISBN 13 : 9783642230677
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Couverture rigide
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Etat : Like New. Like New; Hardcover; Close to new condition; Covers are still glossy with "straight" edge-corners; Unblemished textblock edges; The endpapers and all text pages are bright and unmarked; Binding is tight with a straight spine; This book will be shipped in a sturdy cardboard box with foam padding; Medium Format (8.5" - 9.75" tall); Red covers with title in white lettering; 2012, Springer-Verlag Publishing; 300 pages; "Models of Science Dynamics: Encounters Between Complexity Theory and Information Sciences (Springer Complexity: Understanding Complex Systems)," by Andrea Scharnhorst, et al. N° de réf. du vendeur SKU-586AK01907211
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Models of Science Dynamics: Encounters Between Complexity Theory and Information Sciences (Springer Complexity: Understanding Complex Systems)
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Models of Science Dynamics
Edité par
Springer Berlin Heidelberg Jan 2012, 2012
ISBN 10 : 3642230679
ISBN 13 : 9783642230677
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 300 pp. Englisch. N° de réf. du vendeur 9783642230677
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Models of Science Dynamics : Encounters Between Complexity Theory and Information Sciences
Edité par
Springer, 2012
ISBN 10 : 3642230679
ISBN 13 : 9783642230677
Ancien ou d'occasion
Couverture rigide
Vendeur : Buchpark, Trebbin, Allemagne
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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 300 | Sprache: Englisch | Produktart: Bücher | 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. N° de réf. du vendeur 10933036/12
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Models of Science Dynamics-Encounters Between Complexity Theory and Information Sciences
Edité par
Springer Berlin Heidelberg, 2012
ISBN 10 : 3642230679
ISBN 13 : 9783642230677
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Edited and Authored by leading researchers in the fieldFirst interdisciplinary treatment of this topic and the interface of information and systems sciences, scientometrics and social complex networksAddresses a wider academic and profes. N° de réf. du vendeur 5053095
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Models of Science Dynamics
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Models of Science Dynamics
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Models of Science Dynamics
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Models of Science Dynamics
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Springer, Springer Vieweg Jan 2012, 2012
ISBN 10 : 3642230679
ISBN 13 : 9783642230677
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 300 pp. Englisch. N° de réf. du vendeur 9783642230677
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