Schnädelbach et al 2019 - Adaptive Architecture and Personal Data - author version.pdf (974.88 kB)
Download file

Adaptive architecture and personal data

Download (974.88 kB)
journal contribution
posted on 07.05.2019, 12:07 authored by Holger Schnadelbach, Nils Jager, Lachlan Urquhart
Through sensors carried by people and sensors embedded in the environment, personal data is being processed to try to understand activity patterns and people’s internal states in the context of human-building interaction. This data is used to actuate adaptive buildings to make them more comfortable, convenient, and accessible or information rich. In a series of envisioning workshops, we queried the future relationships between people, personal data and the built environment, when there are no technical limits to the availability of personal data to buildings. Our analysis of created designs and user experience fictions allows us to contribute a systematic exposition of the emerging design space for adaptive architecture that draws on personal data. This is being situated within the context of the new European information privacy legislation, the EU General Data Protection Regulation 2016. Drawing on the tension space analysis method, we conclude with the illustration of the tensions in the temporal, spatial, and inhabitation-related relationships of personal data and adaptive buildings, re-usable for the navigation of the emerging, complex issues by future designers.

Funding

This work has been supported by the University of Nottingham through the Nottingham Research Fellowship ‘The Built Environment as the Interface to Personal Data’ and through EPSRC Grants EP/M000877/1, EP/P505658/1, and EP/M02315X/1.

History

School

  • Architecture, Building and Civil Engineering

Published in

ACM Transactions on Computer-Human Interaction

Volume

26

Pages

1 - 31

Citation

SCHNADELBACH, H., JAEGER, N. and URQUHART, L., 2019. Adaptive architecture and personal data. ACM Transactions on Computer-Human Interaction, 26 (2), Article No. 12.

Publisher

© Association for Computing Machinery (ACM)

Version

AM (Accepted Manuscript)

Publication date

2019

Notes

© ACM 2019. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Computer-Human Interaction, http://dx.doi.org/10.1145/3301426.

ISSN

1073-0516

Language

en