Evaluation of Complexity Issues in Building Information Modeling Diffusion Research

Liao, Longhui; Zhou, Kaixin; Chen, Fan; Ma, Yuanyuan

doi:10.3390/su14053005

Cited by 12 publications

(7 citation statements)

References 73 publications

(96 reference statements)

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“…Nevertheless, the integration of BIM models in the heritage conservation framework is still a significant challenge due to the complexity of managing a relevant amount of geometric data (Liao et al, 2022) and related semantic information.…”

Section: Related Workmentioning

confidence: 99%

From 3d Surveying Data to Bim to Bem: The Incube Dataset

Roman,

Farella,

Rigon

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In recent years, the improvement of sensors and methodologies for 3D reality-based surveying has exponentially enhanced the possibility of creating digital replicas of the real world. LiDAR technologies and photogrammetry are currently standard approaches for collecting 3D geometric information of indoor and outdoor environments at different scales. This information can potentially be part of a broader processing workflow that, starting from 3D surveyed data and through Building Information Models (BIM) generation, leads to more complex analyses of buildings’ features and behavior (Figure 1). However, creating BIM models, especially of historic and heritage assets (HBIM), is still resource-intensive and time-consuming due to the manual efforts required for data creation and enrichment. Improve 3D data processing, interoperability, and the automation of the BIM generation process are some of the trending research topics, and benchmark datasets are extremely helpful in evaluating newly developed algorithms and methodologies for these scopes. This paper introduces the InCUBE dataset, resulting from the activities of the recently funded EU InCUBE project, focused on unlocking the EU building renovation through integrated strategies and processes for efficient built-environment management (including the use of innovative renewable energy technologies and digitalization). The set of data collects raw and processed data produced for the Italian demo site in the Santa Chiara district of Trento (Italy). The diversity of the shared data enables multiple possible uses, investigations and developments, and some of them are presented in this contribution.

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Section: Related Workmentioning

confidence: 99%

From 3d Surveying Data to Bim to Bem: The Incube Dataset

Roman,

Farella,

Rigon

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…This is a version of the classical theory of diffusion of innovation (Rogers 2003) and the theory of lead users in innovation (von Hippel 1986): the early adaptors set the course; the majority will learn from their experience and the overall system keeps moving to higher levels of optimality. Analysis of actual adoptions of BIM in AEC reveals that this type of adoption is only one of many (see Succar and Kassem, 2015;Liao et al 2022).…”

Section: New Tools For Bottom-up Systemsmentioning

confidence: 99%

How typical is your project? The need for a no-model approach for information management in AEC

El-Diraby¹

2023

ITcon

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This paper discusses the merit of using a no-model approach (no common product models or ontologies, etc.) for managing information in the AEC. It proposes an option for such an approach through the generation and analysis of semantic and social networks of communication between project stakeholders. The proposed approach advocates for a bottom-up discovery of knowledge constructs from stakeholder communication. Knowledge constructs are mini two-mode networks containing, on the one hand, clusters of concepts that appear frequently in the semantic networks of stakeholder communication; and, on the other hand, the social networks of stakeholders discussing these concepts. Using common models (such as IFC) has several limitations, including inflexibility to recognize and accommodate project contexts (which vary constantly), inability to timely capture the emergence of knowledge, and the scope creep problem (the ever-existing need to add more concepts to the common model from within and outside ACE domain). The no-model approach presented here is meant to complement and not replace the established model-based approach. This approach is built on the belief in the ontological agency of project stakeholders: knowledge is a social phenomenon that emerges through interactions between people. It advocates a shift from a top-down format where experts or standards clearinghouses tell (force) practitioners what should be true about their project. In every project, stakeholders customize (the structure of) established knowledge and adopt elements from emerging knowledge to address project-specific needs. They use the more superior intelligence (the human one) to innovate a ‘model of what they know’ to guide the management of the project in a manner specific to its context. By studying projects’ communication, we tell (inform) project stakeholders what knowledge constructs can be found in their communication. Unlike generic/static models, the resulting knowledge constructs are by default sensitive to project conditions. We should re-design our information management systems to be able to recognize and adaptively use the constructs established by project teams to facilitate their sharing of data (along with the established scheme, such as IFC). Relatedly used constructs can be nominated as AEC-wide prototype constructs, representing what we know about a typical project. At the initiation of a new project, these can be the starting scheme used by information and communication systems. As the project evolves and the project's own constructs are generated, the project-specific constructs should guide the flow of information. Contrasting project constructs against prototypes should inform the stakeholders of not only what is factual about their view/model of knowledge, but also how unique are they (from generic/base knowledge). This approach to no-model thinking is advantageous for several reasons. First, addressing the model rigidity problem. Because of the increasing complexity of projects, no single/standardized model can capture all contexts. Second, the increasing need for handling project unstructured data. The proposed approach helps formalize knowledge constructs from such data using network science. Third, recognizing and tracking the evolutionary nature of knowledge. Fourth, supporting innovation: instead of forcing knowers (people) to comply with a static model of reality, the new approach encourages them to imagine new possible futures/ worlds—after all, the true essence of digital twinning is to virtualize futures not just to digitize the present.

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“…Looking ahead, Liao et al, [34] propose potential avenues for future research, encompassing inquiries such as analysing the mutual development between collaborative networks and BIM artifacts, refining the Caliber of intricate networks grounded in BIM, comprehending the postadoption behaviours of BIM within intricate environmental scenarios, and formulating strategies for mitigating complexity through BIM-centric approaches. In addition to these studies, other influential work by Mostafa et al, [35] has also contributed to the growing body of knowledge on the application and benefits of BIM in the construction industry.…”

Section: Bim In Green Building Cost Controlmentioning

confidence: 99%

The efficacy of building information model in cost control of green buildings in Shanghai

Shi Yangle,

Khoo Terh Jing,

Chen Siyao

et al. 2023

ARASET

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With the rapid development of modern cities, green buildings have become an important way to reduce energy consumption and environmental impact. The focus of the industry has shifted towards controlling the costs associated with these green buildings. As a solution, Building Information Modelling (BIM), an integrated digital tool, has gained widespread usage in the cost control of green buildings, including in the city of Shanghai. As a centre city of China, Shanghai has both prospects and challenges in the field of green building cost control, it is extremely important to conduct this comprehensive study in Shanghai. Therefore, the primary objective of this study is to delve into the impact of BIM on the cost control of green buildings in Shanghai and unveil its effect during the implementation process of green building projects. To achieve this goal, the author used qualitative research and conducted in-depth interviews with engineers who have used BIM technology in various green building projects. The interviews explored the application of BIM and its effect on controlling costs. The findings of this study reveal that BIM has had a significantly positive impact on the cost control of green buildings in Shanghai. By implementing BIM, the efficiency of cost control has been enhanced throughout the entire life cycle of these environmentally friendly structures. This improvement stems from the ability of BIM to provide accurate and detailed information about the building's design, construction, and operation, enabling better decision-making and resource allocation. The implications of this study are twofold. First, it helps to theoretically understand the impact of BIM on green building cost control, especially in the context of Shanghai. This adds to the existing body of knowledge and furthers research in the field. Secondly, this study also fills the research gap of BIM in the cost control of green building projects in Shanghai.

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Evaluation of Complexity Issues in Building Information Modeling Diffusion Research

Cited by 12 publications

References 73 publications

From 3d Surveying Data to Bim to Bem: The Incube Dataset

From 3d Surveying Data to Bim to Bem: The Incube Dataset

How typical is your project? The need for a no-model approach for information management in AEC

The efficacy of building information model in cost control of green buildings in Shanghai

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