Abstract
The increasing amounts of data in the urban environment and the rise of data-driven design practices are generating an emerging paradigm of smart city planning. In response, this chapter addresses issues of mobility, data, and inhabitation within contemporary speculative architecture and urban informatics. Drawing on the “Future City Glasgow (http://futurecity.glasgow.gov.uk.)” project, this chapter argues that the study of temporary habitation units will be instrumental in addressing two significant real-world issues affecting future cities, namely, mobility and migration. Focusing on the reuse of ‘personal data’, this research explores potential solutions for siting temporary living units within cities, and suggests a new system of short-term habitation that accommodates the needs of mobile citizens, such as mobile students. The proposed system follows the concepts and ideas of post-Fordism (Post-Fordism term in this text refers to the decentralization and “decentred society” and as characterized by Albertsen (1988).) architectural history in urban dynamics and housing strategies, and adopts the process of “Uberization” as an interactive, decentralized system of accommodation provision. Semi-autonomous habitation units are proposed as part of an interactive architectural system, which situates those units in response to individuals’ personal data. The aim of this research was twofold: (a) elaborating on personal data considering its limitations, concerns, and potentialities within creative architectural practice, and (b) addressing data-driven interventions within the urban environment. The ‘personal data’ used in this research was obtained from two sources, Instagram and Airbnb (The access to the data was limited to information on the number of active posts in each location and the location ID (latitude and longitude). The data protection and ethical standards were followed according to the data protection regulation on both sources.). Information processed from both sources was limited to an aggregation of geo-tagged online activities, (Instagram: number of hashtags and Airbnb: number of listings.) which was mapped and illustrated as ‘locative data intensities’. The research contributes by discussing these key questions: (1) How can real-world concerns such as mobility and migration be addressed through a narration of data analytics in smart city planning?; (2) What is the position of personal data in speculative urban informatics and the built environment?; (3) What are the limitations and potentialities of personal data in smart cities’ approaches towards a sustainable urban environment?
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Notes
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Socialbitevillages.co.uk, 2017.
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I refer to the data used in the architectural and urban practices as ‘data practice(s)’ which engages relative information from data sources to propose data-driven architectural interventions.
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Howeleryoon.com (2017).
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More factors: academic centres, privacy and location.
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Application Program Interface (API) is a set of purposes along with processes that permit the creation of apps that access the features or information of application, system, or other services.
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The number of recorded online input from individuals based on their location information in the time of online sharing.
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The number of hashtags in each location in the city regardless of the users’ identification information.
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Valency refers to a words’ potential embedded nature, which here is referring to the affectionate rate of the word.
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Personal information which is attached to a geographical location. Cambridge Dictionary defines geotagged as: a piece of electronic data that shows where someone or something is and can, for example, be attached to a photograph or comment on social media. The studied data in this chapter is identified locally and therefore is geotagged.
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This information can be obtained through a designed field study with the consent of the studied population or from the open source online official sources.
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Like heatmaps and bubble maps which show the quantitative data per location and the size or the intensity of the colour on the map is directly related to the number of recorded geotagged data.
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Chapter “A city is not a galaxy”: Understanding the city through urban data in the book “data and the city” (Kitchin 2014).
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Karam, R. (2019). Millennial Nomads, Uberization and Semi-autonomous Pods. In: Schnädelbach, H., Kirk, D. (eds) People, Personal Data and the Built Environment. Springer Series in Adaptive Environments. Springer, Cham. https://doi.org/10.1007/978-3-319-70875-1_4
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