Building information modeling (BIM) is a powerful methodological approach for designers that has revolutionized the field of architecture and construction for some years now, minimizing errors and making the entire design, construction, and management process more efficient. The first results have been so encouraging that many countries, from Europe to the United States to Asian countries, have adopted specific regulations to promote its development and use. BIM models are based on the Industry Foundation Classes (IFC) standard, i.e., an object-based file format with a data model developed by building SMART to facilitate interoperability. Objects are characterized by properties, such as geometry, material, cost, and all related construction process information, such as scheduling or the maintenance process. The 3D modeling of these objects geometric information is parametric, in order to make the design more flexible. This research work offers an insight into the possibilities offered by different BIM-based tools for parametric modeling applied in the railway sector whereby an example of a railway section model is presented. Indeed, the focus will be on the creation of parametric objects representing railway components, as existing BIM object libraries lack them in the IFC2 × 3 standard format.

Intervention projects for historical buildings depend on the quality of multidisciplinary data sets; their collection, structure, and semantics. Building information model (BIM) based workflows for historical buildings accumulate some of the data sets in a shared information model that contains the building’s geometry assemblies with associated attributes (such as material). A BIM model of any building can be a source of data for different engineering assessments, for example, solar and wind exposure and seismic vulnerability, but for historic buildings it is particularly important for interventions like conservation, rehabilitation, and improvements such as refurbishment and retrofitting. When the BIM model is abstracted to a semantic model, enabling the use of semantic technologies such as reasoning and querying, semantic links can be established to other historical contexts. The semantic technologies help historic building experts to aggregate data into meaningful form. Ontologies provide them with an accurate knowledge representation of the concepts, relationships, and rules related to the historic building. In the paper, we are proposing an improved workflow for the transformation of a heritage BIM model to a semantic model. In the BIM part the workflow demonstrates how the fully parametric modelling of historical building components is relevant, for example, in terms of reusability and adaptation to a different context. In the semantic model part, ontology reuse, reasoning, and querying mechanisms are applied to validate the usability of the proposed workflow. The presented work will improve knowledge-sharing and reuse among stakeholders involved in historic building projects.

The intelligent management of built cultural heritage, including heritage buildings, requires common semantics in the form of standardized ontologies to achieve semantic interoperability. Foundational ontologies should be reused when building new ontologies, as they provide high-level terms; however, candidate foundational ontologies should be evaluated for quality and pitfalls. Simple metrics (e.g., number of concepts) are easy to obtain with existing tools. Complex metrics such as quality of ontology structure, functional adequacy, transferability, reliability, compatibility, maintainability, and operability, are defined in recent ontology evaluation frameworks; however, these do not evaluate interoperability features. The paper proposes an improved framework for an automated ontology evaluation based on the OQuaRE framework. Our approach improved some of the metrics of the OQuaRE framework and introduced three metrics for assessing the interoperability of the ontology in question (Externes, Composability, and Aggregability). In the experimental section, the framework is validated in an evaluation of cultural heritage information ontology (CIDOC CRM—ISO 12217:2014) with the use of new software for ontology evaluation. The detailed results reveal that the ontology is minimally acceptable and that the improved evaluation framework efficiently integrated interoperability metrics. Recommendations for the improvement of the cultural heritage information ontology are described in the Discussion and Conclusions section.

The duplication of semantic data modelled in different disciplines poses interoperability challenges. Information models that benefit from the application of standards that enable data reusability and prevent redundancy and misuse should be compatible, particularly when different systems are used in the same domain-specific area, as in the case of public transportation. Transportation information models, leading and providing reliable and robust public transport services, can nowadays be enriched with information found in building information models devoted to transportation infrastructure. Therefore, in the present paper, a mapping between the standards and technical specifications that support each modelling approach is explored, analysed, and aligned to maximise the best out of the current common practices used. The information from the Industry Foundation Classes IFC specification-based models complements the conceptual and physical transportation models, where Transmodel and NeTEx are well-established, with accurate (as-built) detailed characteristics of the transportation infrastructure (stop places, quays, entrances, access spaces and equipment as ramps, staircases, and escalators). The extraction of topological information stored in IFC models allows for navigation-network extraction, information about spaces, and passages between spaces. A specific public transport case study focused on a train station is detailed to better corroborate and illustrate the advantages and uses of compatible and complementing modelling approaches. As building-information-modelling awareness and use is growing, the validated mapping approach can benefit from the future application of automation procedures.

Mechanical Engineering (ME) includes the design, manufacturing, assembly, and maintenance of mechanical subsystems for Architecture, Engineering, Construction, and Owner-Operator (AECO) projects. The intense adoption of information and communication technology in the AECO started with building product modelling, which was originally pioneered in the ME domain (i.e., automotive industry). The complexity and limited openness of product models paved the way for Building Information Modelling (BIM). Today, BIM workflows require an exchange of interoperable architecture, structure, and MEP/HVAC models and their seamless integration into a shared BIM model. Many specialized ME systems exist (i.e., medical gases and vacuum) for which BIM is not mature enough and where the role of BIM has not yet been studied. Therefore, a comprehensive cross-disciplinary analysis on the mutual influence of the BIM and the ME domain is needed for researchers and professionals. It identifies research fields and trends at the intersection of BIM and ME and analyzes their scope, limitations, and requirements for future extensions of BIM for better integration with ME. The analysis is based on an extensive literature search considering the interdisciplinary nature of ME. The initial collection of papers has undergone a rigorous bibliometric analysis that used a text mining approach for validation. Results show the field “Industry 4.0” as the most prosperous BIM influencing research field, followed by “Energy optimisation” and “Environmental Product Declaration”, while identifying “Geometric optimisation” and “Reinforced material” as the trendiest. Finally, conclusions on the impact of BIM on ME were drawn and 11 research opportunities were identified. This paper provides directions for studies where research is focused on the integration of ME systems in BIM workflows and on the extension of BIM capability to model future ME systems.

The integration of semantic technologies and procedural automation is redefining how infrastructure assets are modeled and managed. Yet, stone-paved roads, common in historical urban centers, remain largely unsupported by existing building information modeling (BIM) standards and tools. This paper presents an innovative, fully automated workflow that bridges this gap by combining a visual programming language (VPL) approach with an ontology-driven semantic framework. Compared to the traditional manual modeling workflow in the BIM-Authoring software Autodesk Civil 3D, which may take several hours, the proposed method generates a complete 3D BIM model by fully automating several modeling operations via a Dynamo graph that takes very short computational times. To achieve this, we developed a parametric modeling pipeline that, based on structured input data, can rapidly generate high-fidelity 3D models of stone-paved roads. To overcome semantic limitations in the Industry Foundation Classes (IFC) schema, we introduce the IFC for stone-paved roads (IFC-SPRO) ontology, designed to enrich geometric models with machine-readable knowledge about modular pavement typologies and maintenance strategies. By converting IFC data into resource description framework (RDF) format and querying it via SPARQL and AI-driven interfaces, the model supports advanced information retrieval for asset management and heritage conservation. The proposed approach not only enhances interoperability and reduces modeling time dramatically but also establishes a scalable foundation for integrating historical road infrastructure into modern digital workflows. Received: 14 April 2025 | Revised: 10 September 2025 | Accepted: 25 September 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data are available from the corresponding author upon reasonable request. Author Contribution Statement Mattia Intignano: Conceptualization, Methodology, Software, Formal analysis, Resources, Writing – original draft,Writing – review & editing, Visualization. Salvatore Antonio Biancardo: Conceptualization, Validation, Formal analysis, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition. Sara Guerra de Oliveira: Conceptualization, Validation, Resources, Writing – review & editing,Visualization. Andrej Tibaut: Conceptualization, Methodology, Software, Resources, Data curation, Writing – review & editing, Supervision. Gianluca Dell'Acqua: Conceptualization, Investigation, Resources, Data curation, Writing – review & editing, Supervision, Project administration.