https://www.arcc-journal.org/index.php/arccjournal/issue/feed Enquiry The ARCC Journal for Architectural Research 2019-12-07T09:26:47-05:00 Philip Plowright pplowright@ltu.edu Open Journal Systems An open access e-journal on architectural research https://www.arcc-journal.org/index.php/arccjournal/article/view/1062 Algorithms and the near future of design 2019-12-07T09:26:44-05:00 Euan Mills Euan.Mills@futurecities.catapult.org.uk <p>Introduction by Silvio Carta<br>In this article Euan Mills, who co-leads the Plantech programme at Connected Places Catapult, reflects on the changes of the design, planning and construction industries. The Connected Places Catapult is a centre devoted to the development and advancement of innovation in cities supported by the UK government. In this multidisciplinary team, planners, urban designers and many other experts collaborate with the public and private sectors, informing the design and construction industries as well as influencing policy-makers. In recent years, Euan and colleagues have been particularly active in engaging with academics, designers and the public in devising new ways in which the planning system in the UK can be improved and updated taking full advantage of new digital technologies and computational approaches to design increasingly available today. Under the title of Plantech (Connected Places Catapult 2019), Euan and colleagues are promoting a new planning agenda whereby in a near future urban data, people’s input and the regulatory system can converge into a seamless framework. Not only this would significantly simplify the planning system and the relationship that residents have with planning authorities and designers but, more importantly, it will synchronise some of the workflows that characterise urban planning and permissions (often with scanned version of old documents, historical paper archives etc.) with the digital assemblage of big data that is the fabric of our cities today.</p> 2019-11-24T00:00:00-05:00 ##submission.copyrightStatement## https://www.arcc-journal.org/index.php/arccjournal/article/view/1058 Learning Algorithms, Design, and computed space 2019-12-07T09:26:45-05:00 Roberto Bottazzi roberto.bottazzi@ucl.ac.uk <p>The paper analyses and speculates on what opportunities and challenges will arise from the introduction of learning algorithms (machine learning, neural networks, etc.) in architectural and urban design. The penetration of such class of algorithms in cities and design disciplines is rapid and profound increasing both the thirst for gathering ever larger and more accurate datasets and raising the prospect of automating tasks currently performed by humans. Whilst it is understood that learning algorithms are essential tools to analyse large datasets, design disciplines have paid far less attention to how such processes are carried out, how spatial data are reformatted by algorithms which largely operate on statistical bases and, most importantly, what image of the city emerges from such processes. To unravel the complexity of the issue, it is first necessary to retrace the ideas informing the emergence of numerical procedures at beginning of the twentieth century and Artificial Intelligence in the 1950’s as they allow us to project a different paradigm of how space can be analysed, structured, and changed. Finally, the paper will offer some points for speculation and further reflection on how the methods put forward through learning algorithms compare to current approaches to digital design; this will foreground their disruptive potential for a radical transformation of urban design, one that could be deployed to tackle some of the most pressing urban issue.&nbsp;</p> 2019-11-24T00:00:00-05:00 ##submission.copyrightStatement## https://www.arcc-journal.org/index.php/arccjournal/article/view/839 The Universal Factory 2019-12-07T09:26:47-05:00 Kevin Rogan negativemetropolitics@gmail.com <p>Critical data studies have made great strides in bringing together data analysts and urban design, providing an extensible concept which is useful in visualizing the role of local and planetary data networks. But in the light of the experience of Sidewalk Labs, critical data studies need a further push. As smart cities, algorithmic urbanisms, and sensorial regimes inch closer and closer to reality, critical data studies remain woefully blind to economic and political issues. Data remains undertheorized for its economic content as a commodity, and the political ramifications of the data assemblages remain locked in a proto-political schema of <em>good </em>and <em>bad </em>uses of this vast network of data collection, analysis, research, and organization. This paper attempts to subject critical data studies to a rigorous critique by deepening its relationship to the history thus far of Sidewalk Labs’ project in Quayside, Toronto. It is broken into sections. The first section discusses the material reality of Kitchin and Lauriault’s (2014) data assemblages and data landscapes. The second section investigates data itself and what its ‘inherent’ value means in an economic sense. The third section looks at the way the understanding of data promoted by the data assemblage effects smart city design. The fourth section examines the role of the designer in shepherding this vision, and moreover the data assemblage, into existence.</p> 2019-11-02T00:00:00-04:00 ##submission.copyrightStatement## https://www.arcc-journal.org/index.php/arccjournal/article/view/582 Data, Data Everywhere, Not a Lot in Sync 2019-12-07T09:26:46-05:00 Pieter Marthinus de Kock pprojexio3@gmail.com <p>Up to 100 billion devices will be seeking to visually map out our existence over the internet by 2020 (UK Government Chief Scientific Adviser 2014). Just as the urban is a forcefield “of spatial transformations… that takes many different morphological forms” (Brenner 2014), this paper explores another underlying forcefield: our visual relationship with data. The most important piece of data, the individual, exists in the city as both prey and predator; having evolved from a “passive aesthetic view of the city” (Appleyard 1979, 144); transformed through shared territory (Evans and Jones 2008); and forged into impressively intricate sets of power relations through collective intentionality (Searle 2011). Through the presentation of self (Goffman, 1969, cited in Appleyard 1979, 146) we inhabit another home: the digital; in which we are simultaneously co-existent and removed by synchronisation of data. Traditionally, the software authoring the physical production of ‘space/hardware’ has been value driven (Raban, 1974, 128, cited in Appleyard 1979, 146). In a parallel universe, algorithms drive the data. For Ellis (2012) it is in the software, that meaning resides. What then is the allure of data to the individual? And what is the allure of the individual to data? It lies arguably in the perception of power and control through meaning (Appleyard, Searle et al.). We seek in the new reality to “discover where the real power lies” (Appleyard 1979, 146). Curiously, the power of data appears to increase the irrelevancy of ownership, between “ours” and “theirs” (Appleyard 1979, 152). This paper analyses past, present, and future states of data production. The data we get from data; data produced from objects; and objects produced from data. In closing, a speculative working hypothesis is presented of visual data production, which hopefully encourages further research reconciling data with meaning in the context of visual sustainability.</p> 2019-11-08T00:00:00-05:00 ##submission.copyrightStatement## https://www.arcc-journal.org/index.php/arccjournal/article/view/1061 Design Implications of Model-Generated Urban Data 2019-12-07T09:26:46-05:00 Ljubomir Jankovic l.jankovic@herts.ac.uk <p>The staggering complexity of urban environment and long timescales in the causal mechanisms prevent designers to fully understand the implications of their design interventions. In order to investigate these causal mechanisms and provide measurable trends, a model that partially replicates urban complexity has been developed. Using a cellular automata approach to model land use types and markets for products, services, labour and property, the model has enabled numerical experiments to be carried out. The results revealed causal mechanisms and performance metrics obtained in a much shorter timescale than the real-life processes, pointing to a number of design implications for urban environments.</p> 2019-11-11T00:00:00-05:00 ##submission.copyrightStatement## https://www.arcc-journal.org/index.php/arccjournal/article/view/1059 Analysis and Simulation of Dynamic Vision in the City 2019-12-07T09:26:45-05:00 Fang Xu Fang.Xu@sdstate.edu <p style="line-height: normal;"><span style="font-size: 12.0pt;">This paper proposes a computer-aided Dynamic Visual Research and Design Protocol for environmental designers to analyze humans’ dynamic visual experiences in the city and to simulate dynamic vision in the design process. The Protocol recommends using action cameras to collect massive dynamic visual data from participants’ first-person perspectives. It prescribes a computer-aided visual analysis approach to produce cinematic charts and storyboards, which further afford qualitative interpretations for aesthetic assessment and discussion. Employing real-time 3D simulation technologies, the Protocol enables the simulation of people’s dynamic vision in designed urban environments to support evaluation in design. Detailed contents and merits of the Protocol were demonstrated by its application in the Urbanscape Studio, a community participatory design course based at Watertown, South Dakota.</span></p> 2019-11-24T00:00:00-05:00 ##submission.copyrightStatement##