Shaping Knowledge

Jamie O’Brien is Research Manager at University College London (UCL) Virtual Environments, Imaging and Visualisation (VEIV), a multidisciplinary research and training centre. Jamie has held positions at the British Library of Political and Economic Science and a leading museum’s education department. He holds a PhD in engineering. Jamie is also a Research Associate at the UCL Centre for Digital Humanities, Visiting Fellow at the Centre for Mobilities Research, Lancaster University, and a Fellow of the Royal Society of Arts, UK.

• DedicationList of figures and tablesFiguresTables AcknowledgementsPrefaceAbout the author1: Introduction and case studyAbstractGeneral introductionSpace and knowledgeDimensions of knowledgeKnowledge representationA case study in socio-spatial changeOverview of the book 2: Innovation, agency and technologyAbstractSpatializing knowledgeSpace and innovationKnowledge as technologyKnowledge as innovationPatterns of innovationSpace, knowledge and powerConclusion 3: The dynamics of innovationAbstractThe social life of innovationRegional dynamicsComplexity and modularityPatterns of adoptionFlowsWavesBifurcationsCriticalityConclusion 4: Modelling knowledge dynamicsAbstractInformation and knowledgeEcologies of innovationEcologies of human developmentNetwork dynamicsNetwork graphsInnovation networksThe topology of regional knowledgeSystem dynamics of innovationsConclusion 5: Modelling socio-spatial agentsAbstractAgency and actionManifolds and messElements of agent behaviourAgency and autonomyCoalitions and decisionsResource allocationSearch and decision-makingModelling with gamesConclusion 6: Case studies in socio-spatial changeAbstractMicro-level socio-spatial change: slum sanitationMicro-level change agentsMeso-level socio-spatial change: remote long-term care servicesSocio-spatial inclusion and mobile platformsMeso-level knowledge integrationExo-level socio-spatial change: Arctic urbanizationExo-level instability and infrastructureAgency and adaptationDilemmas and homophilyBidding and votingKnowledge systemsConclusion 7: Reasoning with graphsAbstractRepresenting knowledge flowVisualization as science and artVisualizations as thought experimentsDrawing relationshipsLogic, symbols and computingComputing for simulationCommunity modelsSpatial distance functionsComplex data modellingSpatial data structuresSurface-network analysisConclusion 8: Decisions and argumentsAbstractConstructing knowledgeDecisions and representationExperience and argumentsBasics of argumentationArgumentation schemesDeriving argumentsApplying argumentationConclusion 9: Directions for adaptive planningAbstractPrinciples of adaptationAdaptation in human systemsManaging knowledge complexityDirections for planningDirections for researchPlanning with implicit knowledgeCalibrating modelsGeneral summaryGeneral conclusions GlossarySources for socio-spatial argumentationBibliographyIndex