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Borrowing from Architecture: sources for Data Science exploration and experience

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Borrowing from Architecture: sources for Data Science exploration and experience

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Architects often utilize iterative, creative processes that help them develop the end effect of their design. Distilled in this creative process is the ability of an architect to take on a variety of positional arguments and organize the details into a finite and meaningful experience. Can the world of architecture offer frameworks for improving the world of data science? I will illustrate a variety of creative methods used by architects and juxtapose these against a variety of issues in Data Science. My aim is to provide alternative methods and ways of thinking to improve your own working processes in order to craft the details of Data Science into a finite and meaningful experience.

Kevin Rooney, Ph.D., is a Data Scientist for Scientific Affairs at PRA Health Sciences International. Dr. Rooney is an interdisciplinarian between science, technology, engineering, art and mathematics with a focus on big data/real world evidence analytics for the healthcare industry. Dr. Rooney has presented at the Salk Institute for the Academy of Neuroscience for Architects and at the Faculty of Medicine and Psychology “Sapienza” University of Rome, Italy for the International Conference on Spatial Cognition. He is published in Frontiers in Psychology titled “Focal and Ambient Processing of Built Environments” and has been invited to publish a review of “Experience, Culture, Cognition and Common Sense” in Intertwining.

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