The use of graph-based asset information is growing in the Architecture, Engineering, Construction, and Operation (AECO) domain. However, there has been no comprehensive investigation into its internal structure, which hinders the efficiency of information querying and knowledge discovery. This study aims to reveal the internal structure of graph-based IFC (Industry Foundation Classes) information, referred to as IFC-Graph, and to assess the impact of graph structure on the efficiency of information querying and knowledge discovery. First, through a close examination of the IFC standard, five levels of detail were identified and proposed for IFC-Graph. Second, methods for generating graphs at each level were developed. Lastly, the impact of graph structure on information querying and knowledge discovery was assessed. The results show that: (1) relations constitute the main framework of graph-based IFC information and are key to efficiently extracting relational information from IFC-Graph; and (2) the proposed five-level framework makes graph-based asset information more practical to use, by increasing flexibility in graph generation and improving the efficiency of graph queries and knowledge discovery.

The lifecycle of the built environment is governed by complex regulations, requirements and standards. Ensuring compliance against these requirements is a complicated process, affecting the entire supply chain and often incurring significant costs, delay and uncertainty. Many of the processes, and elements within these processes, are formalised and supported by varying levels of digitisation and automation. This ranges from energy simulation, geometric checking, to building information modelling based checking. However, there are currently no unifying standards or integrating technology to tie regulatory efforts together to enable the widespread adoption of automated compliance processes. This has left many current technical approaches, while advanced and robust, isolated. However, the increasing maturity of asset datasets/information models, means that integration of data/tools is now feasible. This paper will propose and validate a new approach of solving the problem of automated compliance checking through the use of an ecosystem of compliance checking services. This work has identified a clear research gap. How automated compliance checking in the construction sector can move beyond sole reliance on BIM data, and tightly coupled integration with software tools, to provide an extensible enough system to integrate the current isolated software elements currently used within compliance checking processes. To test this approach, an architecture for an ecosystem of compliance services will be specified. To validate this architecture, a prototype version will be developed and validated against requirements derived from the weaknesses of current approaches. This validation has found that a distributed ecosystem can perform accurately and successfully, whilst providing advantages in terms of scalability and extensibility. This approach provides a route to the increased adoption of automated compliance checking, overcoming the issues of relying on one computer system/application to perform all aspects of this process.

The building permit process is a crucial aspect of the construction industry, as it ensures the safety and compliance of buildings with local regulations. A significant improvement in terms of accuracy, transparency and efficiency would be brought from digitalization, therefore several projects are being developed on the topic. However, to reach high maturity levels, it is necessary to address the several parts of building permit systems in a structured way, by considering the several subsystems composing the main issue thoroughly (e.g., legislative, organizational, technological, procedural). Therefore, this article proposes a taxonomy of building permit systems that can be the reference to guide and assess related developments across diverse countries, allowing their interpretation in a common framework. Different methodologies for taxonomy developments were applied in this study, including a combination of committee approaches and empirical methods, with a final validation against a use case. The obtained high-level taxonomy of building permit systems can serve as a basis for future improvements in the building permit digitalization and could be the basis for an extended ontology.

The use of Building Information Modelling (BIM) models in the design, construction and operation of buildings and infrastructure is leading to a stronger focus on the quality of the models. Models may need correction, enrichment or enhancement to meet the expectations for quality and completeness, especially if models are to be taken as legal documents, for example for regulatory approval. Past work on semantic development has looked at specific scenarios such as scanned geometry or missing classification. This paper describes an innovative unified approach to the documentation of semantic expectations by actors in the AECO (Architectural, Engineering, Construction and Operations) domain and the means to put them into effect. RASE (Requirements, Applications, Selections and Exceptions) semantic mark-up is used to make both the requirements and any supporting resources both human-readable and machine-operable. Two example models from industry, a motorway bridge and a healthcare space, are used to demonstrate applying geometric, schema and classification knowledge. This knowledge is represented in a number of different styles. This extends our understanding of the nature of the knowledge found in dictionaries, classifications and development specifications, demonstrating how this knowledge can be made operable. This bridges the gap between the application of static compliance knowledge and the accurate and efficient application of correction, enrichment and enhancement knowledge.