Towards a comprehensive visual analytics environment for the assessment of socio-ecological factors within architectural design

Keena, Naomi, Ann
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Other Contributors
Diniz, Nancy
Kallipoliti, Lydia
Raugei, Marco
Pinheiro, Paulo
Draper, Joshua
Dyson, Anna, H
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Architectural sciences
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Full Citation
This doctoral research investigates visual analytics as a means to study socio-ecological factors within architectural design, towards the mitigation of adverse environmental impacts. It introduces SEVA (Socio-Ecological Visual Analytics), a proposed new conceptual network of analytical techniques designed to quantify, visualize, characterize and communicate socio-ecological factors within architectural designs offering unprecedented decision-making capacity and the ability to glean new insights towards enhanced faceted data search. With SEVA we propose a new way to simultaneously represent the quantification of energy, life cycle, climate, human and ecosystems health, and socio-economic analyses of different design options, thereby presenting original methods to reveal variations in the designs’ ability to address environmental parameters. This research proposes a set of experimental investigations, which apply these methods: 1) To investigate the viability of applying emergy analysis (EMA) to define a broader scope of the built environmental design process from the work of the geo-biosphere to end-of-life design, and; 2) To determine if such telescopic system analysis, from metadata (descriptive data) to microdata (individual components of the life span) can glean new insights on socio-ecological factors within architectural design at the schematic design stage. The predicted outcomes of the experimental investigations include the simultaneous representation of a comprehensive range of socio-ecological factors in different design options through novel data visualization methods, thereby providing a critical review of the potential for emergy analysis to inform the decision making process during the schematic design phase. The aim of the research is to investigate the potential for annotated visual analytics to enable greater accessibility to extensive and complex data sets that were not previously comprehensible during architectural design towards combating harmful environmental impacts.
School of Architecture
School of Architecture
Rensselaer Polytechnic Institute, Troy, NY
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