Big data on individuals in the architectural design process: combining individual's data with the architects toolset. (18th December 2017)

• Record Type: Journal Article
• Authors: Meekings, Scott; Schnabel, Marc Aurel
• Is Part Of: International journal of parallel, emergent and distributed systems. Volume 32(2017)Supplement 1
• Page Start: S66
• Page End: S72
• Publication Date: 2017-12-18
• Subjects: Big data -- digital identity -- built environment -- social media; Parallel computers -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Computer algorithms -- Periodicals; 004.35
• DOI: 10.1080/17445760.2017.1390091
• Languages: English
• ISSNs: 1744-5760

Abstract

Abstract: It is increasingly common to live in continual flux between reality and virtuality – for architecture this means a dwindling focus on the built environment. For the architectural discipline to be resilient in the face of these rapidly changing user-demands, a proactive relationship with our digital environment is required. It is proposed that the quantity of data that is collected about individuals is becoming large enough to qualify as big data, despite only pertaining to a single person. It has all the hallmarks of the big data phenomon, namely large and diverse fields which with the help of machine learning and cross-referencing can uncover unforeseen patterns. This paper explores how personal big data could be used, with the potential to impact future architectural workflows. We present ways that personal data can be used to develop special connections for architectural design processes. By comparing multiple single-person data sets two key issues are discussed; sourcing relevant data and three-dimensionalizing this data with a particular focus on connections. The paper concludes with a discussion about the future of data as an instrument to aid architectural design processes. Abstract : A DLA algorithm formation, clustering people based on data taken from social media in order to facilitate the special visualization of data for architects.