Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.755589
Title: Conceptual operational model of architecture : an approach for capturing values in architectural practices based on Big Data capabilities
Author: Qabshoqa, M. T.
ISNI:       0000 0004 7428 582X
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2018
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Abstract:
The research focuses on the emerging domain of Big Data and the Internet of Things in the context of architectural design and operation. The profession of architecture relies on the use of data in almost all stages of the building cycle. However, this data is often utilised in a trivial manner, without clearly addressing how the data is utilised, when it is utilised, the value of such utilisation and the impact the data has on the design operations and the overall building. Data in architecture mainly serves as a medium of communication to generate a design. Data can only be as good as the technology available at the time it is gathered. Nevertheless, the role of data has changed with the advancement of digital data technologies such as Big Data and the Internet of Things. Digital data is now a driver for businesses and operations in other industries. The investigation of contemporary data utilisation in architecture design reveals that data is not utilised as a driver for the design in most cases and, when it is utilised as a driver, it is not exploited and is not explicitly addressed as part of the business. A knowledge gap in architecture in addressing the utilisation of data and addressing digital data as a driver in design operations is identified. This identification is supplemented by observing that data-driven operations provide the potential for better and more efficient design and business. To fill this knowledge gap and to build a foundation for data utilisation in architecture, this thesis proposes a Data-Driven Operational Framework for architecture, which is the main output of this research and its main contribution to knowledge. The Data-Driven Operational Framework reveals and explains the required components and operations for employing a data-driven design approach in architectural processes and business. In order to develop such a framework, an investigation of current architectural cases that utilise digital data was completed, which is a crucial part of the research. However, it was not possible to investigate these cases without having a thorough understanding of the state-of-the-art data technologies and an understanding of the existing taxonomy of data and the existing taxonomy of value in architectural operations. To build this taxonomy of data, a literature review investigating the terms data, digital data operations, Big Data and the Internet of Things was conducted. To build the taxonomy of value, a literature review of values, value creation and valuation methods in architecture was performed. Also, this value investigation led to the development of a Digital Value Equaliser, which is a conceptual representation that supports the analysis of values in architectural design cases. The case studies were analysed following the coding techniques of Grounded Theory Methodology. The coding procedures were followed systematically and continuously until data saturation was reached. Reaching data saturation led to the development of the Data-Driven Operational Framework for architecture. The Data-Driven Operational Framework has two theoretical applications, the Data-Driven Levels in architectural operations framework and the Data-Driven Impact on the AEC framework. These two theoretical frameworks are the findings of the second part of the research and add to the research contribution. The Data-Driven Levels framework reveals the different automation levels in utilising data in architectural operations. This framework classifies data operations in architecture into six levels according to how automated they are and the degree of human involvement in each operation. The Data-Driven Impact framework shows the anticipated impact of employing data-driven operations on the existing business and cultural models in architecture, engineering and construction (AEC). This shows the required business and cultural changes in operating an architecture business. The Impact framework supports architects to identify what measures and changes are needed to benefit from the use of data-driven operations in their practices and business.
Supervisor: Kocaturk, Tuba ; Kiviniemi, Arto Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.755589  DOI:
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