Ecosystems Knowledge

Modeling and Analysis Method for Information and Communication

Inbunden, Engelska, 2018

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To analyze complex situations we use everyday analogies that allow us to invest in an unknown domain knowledge we have acquired in a known field. In this work the author proposes a modeling and analysis method that uses the analogy of the ecosystem to embrace the complexity of an area of knowledge. After a history of the ecosystem concept and these derivatives (nature, ecology, environment ) from antiquity to the present, the analysis method based on the modeling of socio-semantic ontologies is presented, followed by practical examples of this approach in the areas of software development, digital humanities, Big Data, and more generally in the area of complex analysis.

Produktinformation

Utgivningsdatum2018-05-11
Mått165 x 239 x 18 mm
Vikt440 g
FormatInbunden
SpråkEngelska
Antal sidor240
FörlagISTE Ltd and John Wiley & Sons Inc
ISBN9781786300645

Tillhör följande kategorier

Systemvetenskap och AI inom Data och IT

Introduction ixChapter 1. Use of the Ecosystem Concept on the Web 11.1. For marketing 21.2. For personal data 41.3. For services and applications 51.4. For dynamic interactivity 71.5. For pictorial analogies 81.6. For the information and communication sciences 12Chapter 2. Ecosystem Modeling: A Generic Method of Analysis 152.1. Hypertextual gardening fertilized by the chaos of John Cage 162.2. An entrepreneurial experience 172.2.1. Objectives 182.2.2. Principle of the game 182.2.3. Motivations 192.2.3.1. Why model a cognitive ecology? 192.2.3.2. The relevance of the garden analogy 202.2.4. Strategic interests and potential benefits 232.3. The maturation of a research project 242.3.1. Evaluating index activity 242.3.2. Folksonomies explorer 282.3.3. Tweet Palette: Semantic mapping 34Chapter 3. Fundamental Principles for Modeling an Existence 413.1. Key concepts for thinking about knowledge ecosystems 423.1.1. The noosphere 423.1.2. Enaction 443.1.3. Complexity 453.1.4. Trajective reason 463.1.5. Agency 473.2. Spinozist principles for an ethical ontology 483.2.1. Spinoza: ethical ontology 493.2.2. Limitations of Spinozism 503.2.3. Three dimensions of existence and three kinds of knowledge 513.2.4. Spinozist symbol politics 553.2.5. Spinozist ethics for the Web 573.2.6. The ontological principles of Descola 583.2.7. Principles of ontological matrices 593.2.8. The Web as analogist ontology 633.2.9. Principles of computer models 673.2.10. From Zeno to Turing via Spinoza 683.2.11. The search for the perfect language 743.3. Semantic knowledge management 773.3.1. The boundaries of ontologies 773.3.2. The semantic sphere IEML 78Chapter 4. Graphical Specifications for Modeling Existences 894.1. Principles of graphical modeling 904.1.1. Unified modeling language 904.1.2. Graphic partitions and diagrams 924.1.3. Fixed image versus dynamic diagram 944.2. Semantic maps 974.2.1. Maps of physical spaces 974.2.2. Time maps 994.2.3. Maps of conceptual spaces 1014.2.4. Interpretation maps 1074.3. Graphical modeling rules 1104.3.1. Physical dimensions 1104.3.2. Actors 1114.3.3. Concepts 1114.3.4. Relations 1124.3.5. Calculating the complexity of an ecosystem 113Chapter 5. Web Platform Specifications for Knowledge Ecosystems 1175.1. The generic management of resources 1195.1.1. Non-digital resources 1195.1.2. Digital resources 1225.1.3. Management of digital resources 1315.2. Principles for developing a Web ecosystem platform 1385.2.1. Databases as a model of the ecosystem 1385.2.2. Algorithmic platform to manage the ecosystem 1535.2.3. Editorial platform for controlling collaborative practices 1575.2.4. Client applications to explore ecosystem views 1625.2.5. From technical specification to the organization of collective intelligence 171Conclusion 173Appendix 185Bibliography 201Index 217