Flows, Bits, and Relationships: Visualizing Social Space


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sg2014 speculates about the implications and opportunities of high urban density. This cluster argues that the complexity of Hong Kong’s dense, interconnected commercial spaces cannot be properly analyzed and represented through conventional methods. In order to develop new ways to visualize and understand this spatial complexity, we propose the use of a novel analytical tool for structuring the various spatial constituents and datasets. The cluster will experiment with organizing data through an interconnected graph database, allowing Ndimensional connectivity across the datasets. Graph databases structure data in networks of nodes (information) and edges (relationships between information). The potential of graph databases lies in their capability to relate diverse datasets with arbitrary relationships.


Based on an aggregation of datasets, cluster participants will explore commercial space configurations and produce a range of subjective maps, along with a curated set of synthetic maps that show averages and trends in the data. Cluster participants will use this analysis to drive new design schemes that embed or modify the interconnected street life of the city, enabling discovery of new relationships through a live and interactive traversal of the database.


Flows, Bits, Relationships: Visualizing Social Space will experiment with organizing data through an interconnected graph database to develop new ways to visualize and understand the spatial complexity of Hong Kong’s dense, interconnected commercial spaces.

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flowbits_steinfeld

Kyle Steinfeld, Assistant Professor specializing in digital design technologies in the Department of Architecture at UC Berkeley, is the author of the "Archtiect's Field Guide to Computation", in contract with Routledge to be published in 2015, and the creator of Decod.es, a platform-agnostic geometry library, and a collaborative community that promotes computational literacy in architectural design. He teaches undergraduate and graduate design studios, core courses in architectural representation, and advanced seminars in digital modeling and visualization. Professionally, he has worked with and consulted for a number of design firms, including Skidmore Owings and Merrill, Acconci Studio, Kohn Petersen Fox Associates, Howler/Yoon, Diller Scofidio Renfro, and TEN Arquitectos. His research interests include collaborative design technology platforms, design computation pedagogy, and bioclimatic design visualization. He holds a Masters of Architecture from MIT and a Bachelor's Degree in Design from the University of Florida.


flowbits_sandoval

Carlos Sandoval is an architect that specializes in computational design, living in Berkeley, CA. He is a researcher at UC Berkeley, and an IDEA Studio Research Fellow at Autodesk in San Francisco. Carlos is a consultant at the Data Lab at UC Berkeley, investigating the convergence of design, data science, and social sciences. In the past four years, Carlos has been a Lecturer at UC Berkeley and at UNAM and has taught computational design seminars and workshops in the United States, Italy, and Mexico, as well as in in events like the ACADIA conference, the Venice Biennale, and the EDRA conference. Carlos holds a Master of Architecture from UC Berkeley, and a Bachelor of Architecture with the Highest Honors from UNAM in Mexico.


flowbits_faichney

John Victor-Faichney is an architect, designer, educator, and software developer who lives in San Francisco, US. John is currently a member of the technical staff at Aditazz, a technology firm in San Francisco that implements computationally enabled scenario based planning for the design of buildings. Prior to this, he was an Associate at Fernau & Hartman Architects. John has been a Lecturer at the University of California, Berkeley teaching computational design and GIS. He has also offered workshops at Diablo Valley College and at the 2012 Association for Computer Aided Design in Architecture (ACADIA) conference at the California College of the Arts (CCA).



 

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