Abstract
Stemming from ongoing research between architecture and the biological sciences, this chapter explores dynamic organization of matter in both a multidimensional microscopic scale human cellular system and a human-scaled perceptual environment from an information theoretical framework. This research examines latent virtual diagrams residing within real dynamic material systems whose generative potential emerges from difference, history, and ultimately the structural information content of spatiotemporal data arrays. Through the development of a design tool, we offer a method for visualizing the underlying formal structures of these data arrays. Currently within LabStudio, a hybrid research and design network, this method is being developed and deployed in the biomedical sciences as a means of analyzing dynamic biological data sets for purposes of determining unique spatiotemporal behavioral signatures in different cell types within unique cellular environments. From a design standpoint, a parallel aim of this research deploys these same information theoretical principles as an analytic technique, specifically in areas of generative design, materiality, and affect as they pertain to organizations of data arrays generated from objects within their environments with and without perceiving subjects, or what we call relative observers.
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- 1.
For the purposes of this text, the term "information" should be taken in the sense of information and communication theory, based on the pioneering 1948 work of Claude Shannon and Warren Weaver [1].
- 2.
For a broad discussion surrounding theories present in contemporary visual perceptual theory, please see Theories of Visual Perception, Third Edition, by Ian E. Gordon [2].
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Acknowledgements
Special thanks to Alexandra Klinger, Christopher Lee, Shawn M. Sweeney, and Mathieu Tamby.
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Lucia, A.P., Sabin, J.E., Jones, P. (2013). Memory, Difference, and Information: Generative Architectures Latent to Material and Perceptual Plasticity. In: Marchese, F., Banissi, E. (eds) Knowledge Visualization Currents. Springer, London. https://doi.org/10.1007/978-1-4471-4303-1_10
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