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Examining the quality and management of non-geometric building information modelling data at project hand-over

机译:在项目移交时检查非几何建筑信息建模数据的质量和管理

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摘要

Through the exponential 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 data of appropriate quality/veracity, to support informed decision making, deliver functionality, facilitate services, or direct strategic 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. This may result 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 broader aspects of this research investigates specifically non-geometric data veracity & associated dimensions of data quality; in order to discover and explore future solutions to resolve current industry data quality assessment challenges. This paper provides feedback from the research focusing on the current state, presenting existing industry challenges and proposes further research areas based on initial findings.
机译:随着全球建筑业采用建筑信息模型(BIM)的指数级增长,以及互连,战略性和数据丰富的解决方案的出现;例如大数据,物联网和智慧城市,与活动和决策相关的重要性依赖于准确的数据输入,交易,分析以及所产生的行动,因此呈指数级增长。不准确的BIM数据的提供可能会对需要充分保证适当质量/准确性的数据的系统和过程产生负面影响,以支持明智的决策,交付功能,促进服务或在已建立的环境中指导战略行动。这项初步研究旨在为可能涉及非几何数据错误的建筑信息模型(BIM)过程的讨论,分析和信息检索提供催化剂。或预计将在项目环境中发生。这可能导致无法描述为代表真相或高质量的数据的传递,因此对于数据用户来说价值不大或用处不大。这项研究的广泛方面专门研究了非几何数据的准确性和数据质量的相关维度;为了发现和探索解决当前行业数据质量评估挑战的未来解决方案。本文提供了针对当前状态的研究反馈,提出了现有的行业挑战,并根据初步发现提出了进一步的研究领域。

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