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Auteur Peter Barbrook-Johnson |
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Titre : Systems mapping: How to build and use causal models of systems Type de document : Monographie Auteurs : Peter Barbrook-Johnson, Auteur ; Alexandra S. Penn, Auteur Editeur : Springer Nature Année de publication : 2022 Autre Editeur : Palgrave Macmillan (Londres, New York, ...) Importance : 186 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-031-01919-7 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] approche participative
[Termes IGN] carte cognitive
[Termes IGN] carte heuristique
[Termes IGN] cartographie dynamique
[Termes IGN] diagramme
[Termes IGN] représentation cartographique
[Termes IGN] représentation mentale
[Termes IGN] réseau bayesienRésumé : (éditeur) This open access book explores a range of new and older systems mapping methods focused on representing causal relationships in systems. In a practical manner, it describes the methods and considers the differences between them; describes how to use them yourself; describes how to choose between and combine them; considers the role of data, evidence, and stakeholder opinion; and describes how they can be useful in a range of policy and research settings. This book provides a key starting point and general-purpose resource for understanding complex adaptive systems in practical, actionable, and participatory ways. The book successfully meets the growing need in a range of social, environmental, and policy challenges for a richer more nuanced, yet actionable and participatory understanding of the world. The authors provide a clear framework to alleviate any confusion about the use of appropriate terms and methods, enhance the appreciation of the value they can bring, and clearly explain the differences between approaches and the resulting outputs of mapping processes and analysis. Note de contenu : Introduction
1- Rich pictures
2- Theory of change diagrams
3- Causal loop diagrams
4- Participatory systems mapping
5- Fuzzy cognitive mapping
6- Bayesian belief networks
7- System dynamics
8- What data and evidence can you build system maps from?
9- Running systems mapping workshops
10- Comparing, choosing, and combining systems mapping methods
ConclusionNuméro de notice : 24095 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie DOI : 10.1007/978-3-031-01919-7 En ligne : https://doi.org/10.1007/978-3-031-01919-7 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102569