Abstract
Building and sustaining our communities is the most significant challenge of our day. This means seeing and understanding the interrelatedness of economies, technologies, physical and natural systems. One way of achieving this objective is visualizing our options using big-data decision spaces where unique systems arerepresented by dynamic flows of data create patterns, relationships and context. As seminal computer scientist Jim Gray articulated in 2003, “big data describes on the one hand extremely large data sets that through analysis generate patterns and associations; on the other hand, it can be understood to encompass all potential data generated by any dynamic process, in short life on Earth as we know it”. This kind of ecological “data literacy” let us see beyond a mechanistic view of the phenomenal world in which the imagined universe is a machine composed of elementary building blocks, to a system view where the dominant model of the material world is a network of systems with interrelated and interdependent patterns of behavior. Adopting the systems’ approach the challenge in designing resilient buildings is: 1) educating architects and engineers capable of using multiple and varied data to create multipart decision spaces, 2) assessing the impact visualizing data will have on all aspects of the building design, construction and fabrication process and 3) making increasingly large data-sets available to the AEC professionals and researchers to asses building performance and its impact on our design, delivery and maintenance of the built environment available.
Highlights
As seminal computer scientist Jim Gray articulated in 2003, “big data describes on the one hand extremely large data sets that through analysis generate patterns and associations; on the other hand, it can be understood to encompass all potential data generated by any dynamic process, in short life on Earth as we know it”
This kind of ecological “data literacy” let us see beyond a mechanistic view of the phenomenal world in which the imagined universe is a machine composed of elementary building blocks, to a system view where the dominant model of the material world is a network of systems with interrelated and interdependent patterns of behavior
This paper looks at the fourth paradigm and its relationship to e-science, potential modes of knowing and their bearing on architecture, engineering and construction, and the AEC of building sciences
Summary
The fourth paradigm according to Gray is a methodological approach to discovery based on data-intensive science beyond experimental and theoretical research and computer simulations of natural phenomena. This isn’t new per se as increasingly complex and larger amounts of data can arguably be considered part of the drive to empiricism in the 19th and the early 20th century science. This paper looks at the fourth paradigm and its relationship to e-science, potential modes of knowing and their bearing on architecture, engineering and construction, and the AEC of building sciences.
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