Information Model Research Articles

Effective integration and models of information: lessons from integrative structure modeling

Integrative structure modeling is a method for using information from multiple sources to compute structural models of biomolecular systems. It proceeds via four steps: (i) defining the model representation, which determines the variables whose values will be computed; (ii) constructing a function for scoring alternative models according to how well they accommodate input information; (iii) searching a space of candidate models for acceptable models; and (iv) analyzing acceptable models to evaluate their fit with input information. These steps are iterated until a model adequate for addressing biological questions is found. In this paper, we draw lessons from integrative modeling about effective integration and about modeling. We describe what it means to integrate information from multiple sources: Integration amounts to distributing information among the four steps of integrative modeling. Theory and data alike can be sources of information; this process thus generates models of information, rather than models of theory or models of data. We then propose heuristics for distributing information and designing multiple iterations of modeling. Effective iteration requires prioritizing the most reliable information and minimizing the time required to obtain an adequate model. Rather than being constructed from theory and assessed using data, models are constructed from any available information and assessed in a coherentist manner.

The impact of BIM on project time and cost: insights from case studies

Building Information Modelling (BIM) has emerged as a transformative tool in the Architecture, Engineering, and Construction (AEC) industries, offering significant potential to improve project efficiency and outcomes. This study explores the impact of BIM implementation on project time and cost by analyzing critical factors such as design errors, unbudgeted changes, Requests for Information (RFIs), labour dynamics, and scheduling across multiple case studies. Quantitative results reveal that BIM adoption reduces project timelines by an average of 20% and costs by 15%, while also decreasing design errors by 30% and RFIs by 25%. Furthermore, BIM enhances collaboration among stakeholders, improves design visualization, and facilitates better risk assessment, leading to more informed decision-making throughout the project lifecycle. These findings are synthesized into a decision-making framework that estimates the probability of errors, evaluates their potential time and cost implications, and ensures alignment with project budgets. The framework serves as a strategic guide for project teams to assess the suitability of BIM for specific projects, thereby optimizing decision-making processes and improving overall project performance. Additionally, the study examines the role of BIM in sustainability by reducing material waste and improving resource allocation. This study addresses a critical gap in the field by systematically evaluating the interrelationships among BIM's impacts on key project parameters, which have often been treated in isolation in prior research. The importance of this work lies in its provision of a structured methodology to harness BIM's capabilities, demonstrating its value in delivering significant time and cost efficiencies while enhancing project quality. By integrating empirical analysis with practical applications, this research contributes to the growing body of knowledge on BIM adoption and provides actionable insights for AEC professionals seeking to optimize project outcomes.

Assessing BIM adoption in the Canadian construction industry: a fuzzy Bayesian network approach

Building information modeling (BIM) adoption has been recognized as a promising development within the construction industry. While BIM offers significant advantages for managing the entire lifecycle of construction projects, its uptake in the Canadian construction sector remains limited. This study employs Bayesian belief networks (BBN) to evaluate the factors influencing the successful implementation of BIM in Canada. Key drivers were identified through a comprehensive literature review, while occurrence probability data were gathered from Canadian construction professionals and analyzed using BBN. The results of this cross-sectional analysis indicate that under current conditions, the probability of successful BIM implementation is relatively low. To improve the likelihood of successful adoption, addressing the shortage of critical BIM resources is essential. The proposed BBN framework serves as a prototype for assessing BIM implementation success across various regions, providing valuable insights for industry stakeholders

Assessing the Efficiency of Integrating BIM and Blockchain to Improve Information Management for Mars Buildings: A SWOT-AHP Analysis

This research investigates integrating Building Information Modeling (BIM) and blockchain technology to enhance building information’s security, reliability, and accuracy in Martian environments. Given the unique challenges posed by extraterrestrial construction, this study evaluates the feasibility of this hybrid approach through a structured SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis. Expert inputs were collected through a comprehensive questionnaire identifying nine strengths, eight weaknesses, eight opportunities, and six threats to implementing BIM and blockchain technology in space projects. The Analytical Hierarchy Process (AHP) was used to prioritize these factors. Findings indicate that the strengths are cost calculation and budgeting (26.21), and the weaknesses are technology complexity (25.488). Increased productivity (19.16) is the most important criterion at the opportunity point, and defects in data security (20.68) are the most important at the threat point. The SWOT analysis places BIM and blockchain integration in a conservative strategy quadrant, indicating that the technology holds significant promise but requires further development and refinement. Ultimately, this research contributes to the growing knowledge about extraterrestrial construction technologies and provides a foundation for developing flexible and autonomous building systems for Martian habitats.

Enhanced image processing and storage for defect evaluation in BIM of inspected steel bridges

Every structure undergoes a maintenance lifecycle, with increasing emphasis on structural health monitoring, defect diagnosis, and repair. As the demand for timely, effective, practical, and cost-efficient solutions grows, new techniques and processes are continually being developed. The traditionally paper-based methods of bridge inspection, defect diagnosis, and repair are evolving into digital processes. The overall efficiency targeted by this digital transformation process can be increased by 35–50 percent when criteria such as time, cost, accuracy and applicability are evaluated. This paper presents an automated data collection and analysis procedure related to structural integrity evaluation. The study focuses on optimizing human-operated inspection procedures by incorporating advanced technologies, such as image processing techniques for defect identification in a digital environment, and integrating defect information into Building Information Modeling (BIM) systems. These focal points and processes, aiming to identify defect identification, and defect information management in BIM environment, are further explored and demonstrated through a case study involving a steel bridge. At the beginning of the study, approximately 160 defect images were collected, examined and some of them were selected for visualization purposes. The authors table a procedure that can be followed, starting with storing defect images and ending with defect visualization in the BIM environment, and present a discussion on the advantages and limits of the process by examining concepts such as automated data collection by drones, machine vision-based damage identification by color detection technique, BIM and Industry Foundation Classes standardisation applied to inspection data.

Developing a Green-BIM team to improve the construction of green buildings in Sri Lanka

Purpose The purpose of the paper is to propose a novel Green-BIM team (GBT) through a framework that would be essential in mitigating barriers to Green-BIM integration.Design/methodology/approach An interpretive stance is adopted for this study. Through a qualitative survey, 25 experts with proficiency in green building construction and building information modelling (BIM) implementation were interviewed. Code-based content analysis was carried out using NVivo12.Findings The findings of this study signified the need for a GBT and proposed architect, client, Green consultant, designer (mechanical, electrical and plumbing [MEP], structural), BIM coordinator, engineer (MEP, structural), project manager, quantity surveyor and facilities manager to be involved in the team representing design phase, construction phase and operational phase.Research limitations/implications The experts were limited to the Sri Lankan context; however, the findings can also benefit countries with socio-economic and cultural backgrounds similar to Sri Lanka.Practical implications Findings will be beneficial for policymakers and industry professionals to promote a BIM-enabled green building environment. The proposed GBT model extends existing theoretical frameworks, emphasising the need for a multi-disciplinary team throughout the entire lifecycle of a green building.Social implications The proposed GBT model aligns with broader societal goals related to sustainable development. This approach provides a sustainable pathway to achieve economic goals for all stakeholders in the construction sector.Originality/value There is a dearth of literature on a GBT to improve the construction of green buildings in Sri Lanka. Thus, the developed model is unique as it presents a novel GBT for the Sri Lankan construction sector. Further, it elaborates roles and responsibilities of team members with comprehensive details on how to mitigate the barriers to Green-BIM integration.

Automatic Monitoring in Construction Projects: Scientometric Analysis and Visualization of Research Activities

Abstract This paper presents a comprehensive scientific analysis of research on automatic monitoring in construction projects. Through a methodical examination of 857 bibliographic records from three databases, we find important trends, novel themes, and key research areas in this field. Our findings reveal that machine learning (ML), building information modelling (BIM), and deep learning are the most the most popular techniques for automatic monitoring. Furthermore, we identify construction technologies and artificial intelligence (AI) as the primary research foci. So, the study uncovers collaboration patterns among researchers and institutions, highlighting key players and their contributions, identifies research gaps and challenges, such as the need for integrating AI, big data, and cloud computing into construction project monitoring, and proposes future research directions to address these challenges and enhance the effectiveness of automatic monitoring systems. By providing a systematic review and insightful analysis, this study contributes to the advancement of construction project monitoring. It offers valuable insights for researchers, practitioners, and policymakers to foster innovation, improve project performance, and ensure sustainable construction practices.

Hyperledger Fabric for the (digitalized) lifecycle of construction products: Applied review on fastening technology

AbstractBlockchain technology is a digital decentralized data ledger recording transactions in an encrypted format. Its implementation can potentially hold significant advantages for the built environment, particularly in manufacturing and building product usage aligned with Building Information Modeling (BIM). This paradigm shift toward decentralized transactions can foster security, reliability, and accountability. Hyperledger Fabric (HLF), an enterprise‐grade distributed ledger, offers a modular, scalable, and confidential digital framework. This article introduces HLF‐based workflows to address inefficiencies in BIM and fastener product lifecycle management, such as fragmented data handling and limited process automation. Leveraging chaincodes linked to BIM models, HLF simplifies, enhances transparency, and automates construction product lifecycle processes. Contract data and execution details are managed through a blockchain stored in a common data environment (CDE) and linked to chaincodes. The article presents the conceptualization and implementation of automated workflows, emphasizing efficiency and transparency. While showcasing successful deployments, it also highlights areas for future improvement and development. The proposed framework represents a pioneering step toward a decentralized cooperative environment in the construction industry, aligning with the transformative potential of blockchain technology.

Simulation-Based Optimization of Crane Lifting Position and Capacity Using a Construction Digital Twin for Prefabricated Bridge Deck Assembly

The growing adoption of off-site construction methods has increased the critical role of mobile cranes within the construction sector. This study develops a Construction Digital Twin (CDT) framework to optimize crane lifting positions and capacities for the installation of prefabricated bridge decks. By integrating 3D site modeling, Building Information Modeling (BIM), and crane simulations within the Unity game engine, the CDT overcomes the limitations of conventional 2D-based planning by providing a three-dimensional representation of site conditions. An exhaustive search method identifies optimal crane configurations, enhancing precision and efficiency. Simulation calibration using video analysis of real bridge deck installations aligns crane speed and cycle times with actual operations, improving reliability. Case studies demonstrate the CDT’s ability to reduce crane operation costs by 27% when employing a smaller capacity crane while maintaining operational efficiency. Additional DFA-focused simulations with varying deck dimensions revealed a potential 10% cost reduction by optimizing crane operations and deck design strategies. The CDT framework supports early-stage planning, reduces operational risks, and contributes to cost-effective and safer construction practices, offering a scalable solution adaptable to various construction scenarios.

The Role of BIM 6D and 7D in Enhancing Sustainable Construction Practices: A Qualitative Study

The construction industry in Kuwait is experiencing a transformative shift with the adoption of Building Information Modeling (BIM) technologies, particularly BIM 6D for sustainability analysis and 7D for facility management. This study investigates the integration of these dimensions to address sustainability challenges in Kuwait’s construction sector, aligning practices with the United Nations’ Sustainable Development Goals (SDGs). Through qualitative interviews with 15 stakeholders—including architects, engineers, and contractors—and analysis of industry reports, policies, and case studies, the research identifies both opportunities for and barriers to BIM adoption. While BIM offers significant potential for lifecycle analysis, waste reduction, and energy efficiency, its adoption remains limited, with only 27% of construction waste recycled. Challenges include high initial costs, a shortage of skilled personnel, and resistance to change. The study highlights actionable strategies, including enhanced regulatory frameworks, university curriculum integration, and professional training programs led by the Kuwait Society of Engineers, to address these barriers. It also emphasizes the critical role of collaboration among government bodies, industry leaders, and institutions like the Kuwait Institute for Scientific Research. Drawing from successful international BIM projects, the findings offer a practical framework for improving sustainability in arid regions, positioning Kuwait’s experience as a model for other Middle Eastern and North African countries. This research underscores the transformative role of BIM technologies in advancing global sustainable construction practices and achieving a more efficient and eco-friendly future.

Challenges and Opportunities for Building Information Modeling in Facility Management: A Case Study from Egypt

The objective of this study is to evaluate the obstacles encountered when using Building Information Modeling (BIM) in Facility Management (FM) within the context of Egypt. The research methodology employs a case study approach, using a single case study to investigate the phenomenon of interest. A comprehensive literature review was conducted, resulting in the identification of 42 challenges to BIM usage in FM. These challenges were classified into five primary groups and formed the basis for a five-point Likert scale questionnaire, which was utilized to collect insights from FM professionals in Egypt. The survey participants included facilities and maintenance managers, as well as BIM employees. The data collected were also analyzed deploying the Impact Effect Index (EI) method. Furthermore, the EI findings indicated that the primary difficulties were the integration of building system design with BIM, the establishment of handover requirements, the integration specifications between the FM and BIM, and securing accurate and reliable data. The category with the highest EI was challenges related to BIM implementation in FM. The research identifies the significant challenges affecting BIM adoption in FM in Egypt, thereby promoting the development of BIM implementation strategies. Consequently, the findings hold practical importance for various stakeholders within the construction sector in Egypt.

Building Information Modelling (BIM) as an Efficient Solution to Middle Eastern Construction Project Delays

The construction and building industry is considered one of the essential players in the economic sector that contributes significantly to creating jobs and generating financial resources. This study provides a review of the construction industry's capability available in the Middle Eastern countries, the development process, and its importance for the economic growth. It analyzes what causes construction projects to go over budget and behind schedule in an attempt to draw conclusions that can be applied to a broader body of research. Delays are costly in terms of time, money, quality, and safety. Some adverse outcomes of project delays are disputes between employer and contractor, lower revenue and productivity, and incomplete projects. This research investigates the reasons behind the construction setbacks in the Middle East and what can be done to rectify the situation. Moreover, it examines the Building Information Modeling (BIM) as a tool to reduce the construction delays. The BIM permits the digital construction of facilities before their physical structure, which aids in time management, reduces risks, improves security, and resolves problems.

Evaluating the Accuracy of Responses by Large Language Models for Information on Disease Epidemiology.

Accurate background epidemiology of diseases are required in pharmacoepidemiologic research. We evaluated the performance of large language models (LLMs), including ChatGPT-3.5, ChatGPT-4, and Google Bard, when prompted with questions on disease frequency. A total of 21 questions on the prevalence and incidence of common and rare diseases were developed and submitted to each LLM twice on different dates. Benchmark data were obtained from literature searches targeting "gold-standard" references (e.g., government statistics, peer-reviewed articles). Accuracy was evaluated by comparing LLMs' responses to the benchmark data. Consistency was determined by comparing the responses to the same query submitted on different dates. The relevance and authenticity of references were evaluated. Three LLMs generated 126 responses. In ChatGPT-4, 76.2% of responses were accurate, which was higher compared to 50.0% in Bard and 45.2% in ChatGPT-3.5. ChatGPT-4 exhibited higher consistency (71.4%) than Bard (57.9%) or ChatGPT-3.5 (46.7%). ChatGPT-4 provided 52 references with 27 (51.9%) providing relevant information, and all were authentic. Only 9.2% (10/109) of references from Bard were relevant. Of 65/109 unique references, 67.7% were authentic, 7.7% provided insufficient information for access, 10.8% provided inaccurate citation, and 13.8% were non-existent/fabricated. ChatGPT-3.5 did not provide any references. ChatGPT-4 outperformed in retrieving information on disease epidemiology compared to Bard and ChatGPT-3.5. However, all three LLMs presented inaccurate responses, including irrelevant, incomplete, or fabricated references. Such limitations preclude the utility of the current forms of LLMs in obtaining accurate disease epidemiology by researchers in the pharmaceutical industry, in academia, or in the regulatory setting.

Digitalized Document Management System for Construction Claims and Disputes to Enhance the Smoothness of Advanced Construction Projects Using the Building Information Modeling Integrated Framework

Digitalized Document Management System for Construction Claims and Disputes to Enhance the Smoothness of Advanced Construction Projects Using the Building Information Modeling Integrated Framework

Influences of BIM-LOD and Geographic-Scale Environmental Impact Factors on embodied emissions: The Norwegian context

Life Cycle Assessment (LCA), grounded in Building Information Modelling (BIM), plays a crucial role in minimizing emissions in the Architeture, Engineering, and Construction (AEC) sector. However, the accuracy of LCA outcomes is significantly influenced by BIM’s Level of Development (LOD) and Geographic-Scale Environmental Impact Factor (GS-EIF). Using a Norwegian Timber Building as a case study, this article explores the effects of BIM-LOD and GS-EIF on LCA embodied emissions of the life cycle stage from Cradle to Gate. The findings reveal that lower BIM-LOD levels, such as LOD 200, tend to underestimate environmental impacts compared to higher LOD levels, like LOD 350. For instance, Global Warming Potential (GWP) can increase by 142% when movingfrom LOD 200 to LOD 350. Conversely, transitioning from Global Generic Environmental Impact Data (GLD) to Site Specific Environmental Impact Data (SFD), GWP can fall by up to 95%. This underscores the critical role of using precise environmental impact data to enhance decision-making and improve a building’s environmental performance. The study recommends starting with BIM-LOD 300 and Country-specific Regional EIF data (CRD) during the design development stages to balance accuracy and practicality. Tracking the transition along the BIM-LCA progress further strengthens the robustness of theLCA results. However, it is essential to note that the findings of this study are specific to Norwegian timber buildings and may not apply universally to other building types or materials. Therefore, further research is needed to validate these findings across different building structural types, geographic regions and environmental contexts.

Evaluation of gestational nonpersistent pesticide exposure with newborn size and gestational length in rural Ghana using a novel time-varying extension of multiple informant models.

Gestational pesticide exposure may negatively affect newborn outcomes. Prior results evaluating nonpersistent pesticides are inconsistent. To examine associations between gestational exposure to nonpersistent pesticides and newborn outcomes and identify critical windows of susceptibility. In a Ghanaian pregnancy cohort, we measured select biomarkers of organophosphate, pyrethroid, and herbicide pesticides in repeated urine samples (1-5/participant). We developed a new model for assessing critical windows of vulnerability from irregularly-timed measurements of nonpersistent pesticides, leveraging strengths from multiple informant and distributed lag models. We estimated associations of biomarker concentrations with newborn anthropometrics and gestational length, adjusting for confounders and exploring effect modification by infant sex and placental malaria. 1,211 pregnant women contributed 3,786 gestational urinary samples. In models assuming constant associations with exposures across pregnancy, in a given week a doubling of 3-phenoxybenzoic acid (pyrethroid biomarker) was associated with a -15.8g difference in birth weight (95% CI:-28.1,-3.6), and a doubling of the 2,4-dichlorophenoxyacetic acid (2,4-D, herbicide biomarker) was associated with an 11.1g increase in birth weight (95% CI:1.0,21.1). In time-varying models, significant associations were identified for pyrethroid exposure measured between weeks 16-27, and for 2,4-D exposure measured during weeks 25-33. Organophosphates were not associated with birth weight. No associations were found for birth length or head circumference for any pesticide. In constant association models, a doubling of weekly 2,4-D was associated with a 0.05week increase in gestational length (95%CI:0.01,0.09); no associations were found with other biomarkers. We identified associations between gestational exposure to nonpersistent pesticides and both birth size and gestational length. Extending multiple informant models to account for the complex data structure allowed us to discern effects in opposing directions by distinct pesticide classes. While estimated effects for a given week were modest, prolonged or repeated exposures could result in larger cumulative impacts.

Digital supervision in construction pollution control: Utilizing advanced information models for enhanced supervision and sustainability

Digital supervision in construction pollution control: Utilizing advanced information models for enhanced supervision and sustainability

BIM for mining - Automated generation of information models using a parametric modelling concept

BIM for mining - Automated generation of information models using a parametric modelling concept

Integration of Building Information Modeling, Geographic Information System, and Augmented Reality for Visualization and Management of Multiple Underground Utilities

Integration of Building Information Modeling, Geographic Information System, and Augmented Reality for Visualization and Management of Multiple Underground Utilities

Automated identification of hazardous zones on construction sites using a 2D digital information model

Automated identification of hazardous zones on construction sites using a 2D digital information model