Examining quality of non-geometric data veracity at project hand-over for BIM data management

Through the expediential global increase of Building Information Modelling (BIM) adoption across the Construction industry, and the emergence of inter-connected, strategic and data-rich solutions; such as Big Data, the Internet of Things and Smart Cities, the importance associated with activities and decisions reliant on exact data input, transaction, analysis and resulting actions becomes exponentially magnified. The supply of inaccurate BIM data may negatively impact on systems and processes that require fully assured and data of appropriate quality / veracity, in order to support informed decision making, deliver functionality, facilitate services, or direct actions within the built environment. This preliminary research intends to provide a catalyst for discussion, analysis and information retrieval relating to Building Information Modelling (BIM) processes where non-geometric data errors may; or are predicted to occur within a project environment, resulting in the delivery of data that cannot be described as representing truth or of good quality, and therefore of little value or use to the data user. The wider aspects of this research is investigating specifically non-geometric data veracity & associated dimensions of data quality; in order to discover and explore future solutions to resolve current industry challenges. This paper provides feedback from the research focusing on current state and presents existing industry challenges and proposes further research areas based on initial findings.

Proceedings © International Congress of Architectural Technology / Robert Gordon University 2018