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This study establishes an ontology-based framework for rework risk identification (RRI) by integrating heterogeneous data from the information flow of the prefabricated construction (PC) process. The main objective is to enhance the automation level of rework management and reduce the degree of reliance on human factors and manual operations.

The proposed framework comprises four levels aimed at managing dispersed rework risk knowledge and integrating heterogeneous data. The functionalities were realised through an integrated ontology that aligned the rework risk ontology with the PC ontology. The ontologies were developed and edited with Protégé. Ultimately, the potential benefit of the framework was validated through a case study and an expert questionnaire survey.

The framework is proven to effectively manage rework risk knowledge and can identify risk objects, clarify risk factors, determine risk events, and retrieve risk measures, thereby enabling the pre-identification of prefabricated rework risk (PRR) and improving the automation level. This study is meaningful and lays the foundation for the application of other computer methods in rework management research and practice in the future.

This research provides insights into the application of ontology to solve rework risk issues in the PC process and introduces a novel risk management method for future prefabricated project research and practice. The findings have significant theoretical value in terms of enriching the methods of risk assessment and control and the information management system of prefabricated projects.

This paper introduces the problematic of the SBP modeling. Our objective is to provide a conceptual analysis related to the concept of SBP. This facilitates, on the one hand, easier understanding by business analysts and end-users, and one the other hand, the integration of the new specific concepts relating to the SBP/BPM-KM domains into the BPMN meta-model (OMG, 2013).

We propose a rigorous characterization of SBP (Sensitive Business Processes) (which distinguishes it from classic, structured and conventional BPs). Secondly, we propose a multidimensional classification of SBP modeling aspects and requirements to develop expressive, comprehensive and rigorous models. Besides, we present an in-depth study of the different modeling approaches and languages, in order to analyze their expressiveness and their abil-ity to perfectly and explicitly represent the new specific requirements of SBP modeling. In this study, we choose the better one positioned nowadays, BPMN 2.0, as the best suited standard for SBP representation. Finally, we propose a semantically rich conceptualization of a SBP organized in core ontology.

We defined a rigorous conceptual specification for this type of BP, organized in a multi-perspective formal ontology, the Core Ontology of Sensitive Business Processes (COSBP). This reference ontology will be used to define a generic BP meta-model (BPM4KI) further specifying SBPs. The objective is to obtain an enriched consensus modeling covering all generic concepts, semantic relationships and properties needed for the exploitation of SBPs, known as core modeling.

This paper introduces the problem of conceptual analysis of SBPs for (crucial) knowledge identification and management. These processes are highly complex and knowledge-intensive. The originality of this contribution lies in the multi-dimensional approach we have adopted for SBP modeling as well as the definition of a Core Ontology of Sensitive Business Processes (COSBP) which is very useful to extend the BPMN notation for knowledge management.

The paper addresses the issue of change in Wikidata ontology by exposing the role of the socio-epistemic processes that take place inside the infrastructure. The subject of the study was the process of extending the Wikidata ontology with a new property as an example of the interplay between the social and technical components of the Wikidata infrastructure.

In this study, an interpretative approach to the evolution of the Wikidata ontology was used. The interpretation framework was a process-centric approach to changes in the Wikidata ontology. The extension of the Wikidata ontology with a new property was considered a socio-epistemic process where multiple agents interact for epistemic purposes. The decomposition of this process into three stages (initiation, knowledge work and closure) allowed us to reveal the role of the institutional structure of Wikidata in the evolution of its ontology.

This study has shown that the modification of the Wikidata ontology is an institutionalized process where community-accepted regulations and practices must be applied. These regulations come from the institutional structure of the Wikidata community, which sets the normative patterns for both the process and social roles and responsibilities of the involved agents.

The results of this study enhance our understanding of the evolution of the collaboratively developed Wikidata ontology by exposing the role of socio-epistemic processes, division of labor and normative patterns.

The purpose of this study is to develop a domain independent, cost-effective, time-saving and semi-automated ontology generation framework that could extract taxonomic concepts from unstructured text corpus. In the human disease domain, ontologies are found to be extremely useful for managing the diversity of technical expressions in favour of information retrieval objectives. The boundaries of these domains are expanding so fast that it is essential to continuously develop new ontologies or upgrade available ones.

This paper proposes a semi-automated approach that extracts entities/relations via text mining of scientific publications. Text mining-based ontology (TmbOnt)-named code is generated to assist a user in capturing, processing and establishing ontology elements. This code takes a pile of unstructured text files as input and projects them into high-valued entities or relations as output. As a semi-automated approach, a user supervises the process, filters meaningful predecessor/successor phrases and finalizes the demanded ontology-taxonomy. To verify the practical capabilities of the scheme, a case study was performed to drive glaucoma ontology-taxonomy. For this purpose, text files containing 10,000 records were collected from PubMed.

The proposed approach processed over 3.8 million tokenized terms of those records and yielded the resultant glaucoma ontology-taxonomy. Compared with two famous disease ontologies, TmbOnt-driven taxonomy demonstrated a 60%–100% coverage ratio against famous medical thesauruses and ontology taxonomies, such as Human Disease Ontology, Medical Subject Headings and National Cancer Institute Thesaurus, with an average of 70% additional terms recommended for ontology development.

According to the literature, the proposed scheme demonstrated novel capability in expanding the ontology-taxonomy structure with a semi-automated text mining approach, aiming for future fully-automated approaches.

This study aims to propose a collaborative knowledge-based ontological research model for designing a collaborative product development process (PDP) while considering different design for X techniques.

This study follows a thematic literature analysis to identify the key design concepts needed to assess environmental, service, safety, manufacture and assembly, supply chain and quality concerns in developing a collaborative PDP.

The proposed model provides a guide for methodology, engineering and ontology evaluation metrics (verification, assessment and validation). The findings benefit both practitioners and managers because they address the key knowledge taxonomy needed to assist them in storing information, promoting teamwork and making decisions in a collaborative PDP while incorporating various design for X approaches and product life cycles.

This study introduces a novel knowledge-based collaborative ontological research model, which is specifically designed to tackle the challenges of developing collaborative products in the contemporary landscape. The model presents a significant and valuable contribution to the field by introducing an ontological approach for acquiring, representing and leveraging knowledge in a computer-interpretable format to support the design of collaborative products. In addition, it provides a comprehensive guide for evaluating the effectiveness and efficacy of the ontology developed.

This project examines digital modeling strategies for existing buildings. In this context, it aims to question assumptions about the need for geometric accuracy and the efficacy of predefined ontologies. As a counterpoint to prevailing digital modeling strategies, this project proposes a digital modeling approach using a project-specific, emergent ontology.

Nishiki Market, in Kyoto, Japan, is studied as a test case. The emergent-ontology modeling process is introduced with an initial minimal set of operations including basic fold and trim operations applicable to surfaces. As the model develops iteratively, new situations are encountered for which existing rules are insufficient. In response, the model maker’s subjective judgment is invoked to introduce new operations, and ontological rules are allowed to expand.

The emergent-ontology approach, when executed on the Nishiki Market test case, enables representation of specific architectural qualities, highlighting semantic distinctions between digitally modeled elements of real-world features. The modeling approach generated project-specific knowledge, informing disciplinary understanding. Ontological emergence enabled semantic relationships to be disclosed and newly constructed.

The project proposes a novel methodology using an emergent ontology for digitally modeling existing buildings. Instead of remaining within the limitations a predefined ontology, the model maker’s subjective decisions shape the model’s ongoing development. This interpretive approach allows project-specific knowledge generation while challenging prevailing assumptions about accuracy and consistency in digital models of existing buildings.

This study presents an ontological approach to assess the architectural outputs of generative adversarial networks. This paper aims to assess the performance of the generative adversarial network in representing building knowledge.

The proposed ontological assessment consists of five steps. These are, respectively, creating an architectural data set, developing ontology for the architectural data set, training the You Only Look Once object detection with labels within the proposed ontology, training the StyleGAN algorithm with the images in the data set and finally, detecting the ontological labels and calculating the ontological relations of StyleGAN-generated pixel-based architectural images. The authors propose and calculate ontological identity and ontological inclusion metrics to assess the StyleGAN-generated ontological labels. This study uses 300 bay window images as an architectural data set for the ontological assessment experiments.

The ontological assessment provides semantic-based queries on StyleGAN-generated architectural images by checking the validity of the building knowledge representation. Moreover, this ontological validity reveals the building element label-specific failure and success rates simultaneously.

This study contributes to the assessment process of the generative adversarial networks through ontological validity checks rather than only conducting pixel-based similarity checks; semantic-based queries can introduce the GAN-generated, pixel-based building elements into the architecture, engineering and construction industry.

Security assurance evaluation (SAE) is a well-established approach for assessing the effectiveness of security measures in systems. However, one aspect that is often overlooked in these evaluations is the assurance context in which they are conducted. This paper aims to explore the role of assurance context in system SAEs and proposes a conceptual model to integrate the assurance context into the evaluation process.

The conceptual model highlights the interrelationships between the various elements of the assurance context, including system boundaries, stakeholders, security concerns, regulatory compliance and assurance assumptions and regulatory compliance.

By introducing the proposed conceptual model, this research provides a framework for incorporating the assurance context into SAEs and offers insights into how it can influence the evaluation outcomes.

By delving into the concept of assurance context, this research seeks to shed light on how it influences the scope, methodologies and outcomes of assurance evaluations, ultimately enabling organizations to strengthen their system security postures and mitigate risks effectively.

This paper aims to explore how young students experience the contribution of a pedagogical assemblage based on design thinking (DT) while contributing to the transition to a more just and sustainable university.

This qualitative research considers the case of two pedagogical experiences developed at Universitat Politècnica de Valencià, Spain. In both experiences, a methodological proposal that includes practices of care, just transitions and DT was implemented. The data obtained through in-depth interviews, surveys and digital whiteboard labels was analyzed under the lens of three relational categories in the context of sustainability.

Learnings are acquired through five categories: place-based learning, prior learning, embodied learning, collaborative teamwork and intersectionality. The research shows how the subjective knowledge of young students positions them as co-designers and leaders of a University that drives a more just and sustainable transition.

The originality of the paper lies in the shift of DT from a human-based approach to a justice-oriented relational approach.

The built environment is taking enormous leaps towards its digitalization. Computer-aided tools such as building information modeling (BIM) are found in the forefront of this evolution, playing a critical role in creating the foundations for the upcoming development of smart low-carbon cities. However, the potential of BIM is still untapped – links will need to be created among the available and forthcoming methodologies under one integral operational system. The purpose of this paper is to present an integrated BIM-based life cycle-oriented framework for achieving sustainable constructions at the pre-construction phase. The developed framework represents an example of the approaches that the construction industry will need to adopt to integrate the different tools under an integrated smart city context.

The methodological approach follows the development of four same-volume different-configuration three-dimensional BIM designs, which are coupled with life cycle assessment (LCA) tools for establishing sustainable building design.

The results of this paper indicated that the choice of building design and shape can play a significant role in reducing the embodied energy and embodied carbon of buildings, achieving a reduction of up to 15% compared to a reference building of same volume and gross floor area.

The originality of this paper is found in its approach application by coupling three-dimensional BIM models with LCA data, the use of reinforcement detailing in an nD BIM study and the employment of country-specific LCA databases.