Ontology-Based Building Information Modeling

Indoor navigation supported by the Industry Foundation Classes (IFC): A survey

The Life Cycle Assessment (LCA) of buildings is an important evaluation method for the environmental quality of a building and its impact on climate and environment. However, the efforts required are very high and cost-intensive. Whole-building LCAs are therefore usually only used as theoretical evidence after completion of a certified building. The potential for full environmental optimization in early project phases is therefore not used in practice. New digital planning methods such as Building Information Modeling (BIM) offer the possibility of integrating and linking much of the information required for a whole-building LCA when creating a digital building model, which should be incorporated by all participants in the planning right from the start. Technical, organizational and contractual prerequisites must be (further) developed so that a whole-building LCA can be applied earlier and more easily with the aid of the BIM method. Within the framework of this work, primarily issues and their technical improvements of the official German LCA database ÖKOBAUDAT and German green building certification systems BNB/DGNB are presented. Based on the open BIM standard of the IFC data model, current fundamentals will be examined to adapt ÖKOBAUDAT aiming to simplify BIM integrated calculation of whole-building LCAs. In this context, concrete recommendations for action to extend the IFC data model and ÖKOBAUDAT will be discussed.KeywordsWhole-building life cycle assessmentBuilding information modeling (BIM)Industry foundation classes (IFC)

IFC (Industry Foundation Classes) has been widely adopted in BIM (Building Information Modeling) for information interchange. Actual data exchange relies heavily on the IFC support of target application. This paper introduces a generic way of accessing IFC model business data as needed. In this paper, we will present 1) a concept and a method to define tabular views of IFC data for downstream uses, 2) an algorithm to transform IFC data to defined tabular views, 3) a tool of exporting transformed results to ODBC compliant applications e.g. MS Office etc. in the context of i-model, a selfdescribing, read-only graphic container containing information with engineering precision, and 4) a case study to create COBie handover from IFC using this tool.

The IFC File Analyzer software generates a spreadsheet or a set of CSV (comma-separated value) files from an IFC file. IFC (Industry Foundation Classes) is the data exchange standard used to facilitate interoperability in the building and construction industry. IFC is developed by buildingSMART and is an ISO standard—ISO 16739. Typical IFC viewers show avisualization of the building represented by the IFC file. The user can drill down to the individual attributes for a single building object. However, there is no way to view all of the entities and their attributes at once. The IFC File Analyzer provides this capability by creating a spreadsheet or CSV files from the IFC file. In the spreadsheet, a worksheet is created for each type of IFC entity in the file. Every row in the worksheet contains the attributes for an instance of an IFC entity. Multiple IFC files can be analyzed at once to compare entity usage. There are options to select which types of IFC entities are processed and to report some of the IFC entity Inverse relationships.

The assessment of Industrialized Building System (IBS) adoption in construction projects—a critical metric for evaluating prefabrication levels and construction modernization—remains largely manual, time-intensive, and prone to inconsistencies, with practitioners typically requiring 4–8 h to evaluate a single building using spreadsheet-based frameworks and visual documentation review. This paper presents a novel AI-enhanced workflow architecture that automates IBS scoring through systematic processing of Industry Foundation Classes (IFC) building information models—the first documented integration of web-based IFC processing, visual workflow automation (n8n), and large language model (LLM) reasoning specifically for construction industrialization assessment. The proposed system integrates a web-based frontend for IFC file upload and configuration, an n8n workflow automation backend orchestrating data transformation pipelines, and an Azure OpenAI-powered scoring engine (GPT-4o-mini and GPT-5-0-mini) that applies Construction Industry Standard (CIS) 18:2023 rules to extracted building data. Experimental validation across 136 diverse IFC building models (ranging from 0.01 MB to 136.26 MB) achieved a 100% processing success rate with a median processing duration of 61.62 s per model, representing approximately 99% time reduction compared to conventional manual assessment requiring 4–8 h of expert practitioner effort. The system demonstrated consistent scoring performance with IBS scores ranging from 31.24 to 100.00 points (mean 37.14, SD 8.84), while GPT-5-0-mini exhibited 71% faster inference (mean 23.4 s) compared to GPT-4o-mini (mean 80.2 s) with no significant scoring divergence, validating prompt engineering robustness across model generations. Processing efficiency scales approximately linearly with file size (0.67 s per megabyte), enabling real-time design feedback and portfolio-scale batch processing previously infeasible with manual methods. Unlike prior rule-based compliance checking systems requiring extensive manual programming, this approach leverages LLM semantic reasoning to interpret ambiguous construction classifications while maintaining deterministic scoring through structured prompt engineering. The system addresses key interoperability challenges in IFC data heterogeneity while maintaining traceability and compliance with established scoring methodologies. This research establishes a replicable architectural pattern for BIM-AI integration in construction analytics and positions LLM-enhanced IFC processing as a practical, accessible approach for industrialization evaluation that democratizes advanced assessment capabilities through open-source workflow automation technologies.

Building Information Modelling (BIM) has been increasingly integrated with Artificial Intelligence (AI) solutions to automate building construction processes. However, the methods for effectively transforming data from BIM formats, such as Industry Foundation Classes (IFC), into formats suitable for AI applications still need to be explored. This paper conducts a Systematic Literature Review (SLR) following the PRISMA guidelines to analyse current data preparation approaches in BIM applications. The goal is to identify the most suitable methods for AI integration by reviewing current data preparation practices in BIM applications. The review included a total of 93 articles from SCOPUS and WoS. The results include eight common data types, two data management frameworks, and four primary data conversion methods. Further analysis identified three barriers: first, the IFC format’s lack of support for time-series data; second, limitations in extracting geometric information from BIM models; and third, the absence of established toolchains to convert IFC files into usable formats. Based on the evidence, the data readiness is at an intermediate level. This research may serve as a guideline for future studies to address the limitations in data preparation within BIM for AI integration.

Future weather scenarios significantly affect indoor thermal comfort, influencing people’s well-being and productivity at work. Thus, future weather scenarios should be considered in the design phase to improve a building’s climate change resilience for new constructions as well as renovations in building stock. As thermal comfort is highly influenced by internal and external thermal loads resulting from weather conditions and building usage, only a dynamic building performance simulation (BPS) can predict the boundary conditions for a thermal comfort analysis during the design stage. As the model setup for a BPS requires detailed information about building geometry, materials, and usage, recent research activities have tried to derive the required simulation models from the open BIM (Building Information Modeling) Standard IFC (Industry Foundation Classes). However, even if IFC data are available, they are often faulty or incomplete. We propose a template-based enrichment of the BPS models that assists with imputing missing data based on archetypal usage of thermal zones. These templates are available for standardized enrichment of BPS models but do not include the required parameters for thermal comfort analysis. This study presents an approach for IFC-based thermal comfort analysis and a set of zone-usage-based templates to enrich thermal comfort input parameters.

The aim of this study is to develop an automated rule-checking application that enables the rapid, transparent, and efficient verification of building design data, created through Building Information Modeling (BIM), in compliance with zoning regulations during the design and approval phases of construction projects in Turkiye. In this context, rules expressed in regulatory texts were transformed into a format adaptable to software using propositional logic, and decision structures were created. Distinctive parameters based on the rules to be checked were assigned to the BIM environment. Model data were exported in the shareable Industry Foundation Classes (IFC) format, and a Python-based software was developed to test the automated rule-checking method on four different sample projects, generating result reports. The findings show that regulatory provisions can be converted into logical structures and compared with Industry Foundation Classes data, making it possible to digitally assess a project’s compliance with regulations. This approach could contribute to enabling public authorities to implement a more effective and transparent control mechanism in the design and approval processes. The originality of the study lies in the successful application of classical propositional logic—despite its lack of complex logical operators—to complex regulatory rules. Moreover, the set of validated propositions not only defines the outcome of the rule check but also provides comprehensive contextual information related to the rule, allowing for a more in-depth evaluation of the results.

Building information model (BIM) is a new emergence in the field of Architecture, Engineering and Construction (AEC) industry, which facilitates detailed digital representation of a building. The BIM archetype describes the details of a building in the Industry Foundation Class (IFC), which is a platform-agnostic, open data model developed by buildingSMART. The BIM data model embeds interoperability and querying facility among its principal traits in support of the AEC industry. The building information is also required by domains outside the AEC industry, to develop a wide variety of applications such as smart building and indoor navigation systems. In such cases, the IFC data model falls short in supporting interaction with applications of external domains other than AEC. The proposed work is aimed to perform a study on various efforts undertaken in the integration of BIM model with external domain querying and reasoning systems, to retrieve details from underlying building models.

The upcoming next generation of the Internet, often referred to as the semantic Web, will bring a lot of new technologies, one of which is the Web ontology language (OWL). One feature of this language is to support interoperability between software applications, including Web services and intelligent agents. Another technology to bring interoperability between software programs is ISO-10303 Standard Exchange of Product data (STEP). The industry foundation classes (IFC) have been developed as a building information model for the building and construction industry using technology from STEP. Converting IFC to OWL can be done on different ways. A unidirectional conversion from an IFC to an OWL has been developed for research purposes. The developed prototype converts not all the IFC data to OWL but supports the search for a more appropriate mapping. As the conversion is not straightforward, reengineering the building model to gain more advantages of functionality offered by OWL has to be investigated.

Recently, interoperability between BIM (Building Information Model) and BEM (Building Energy Model) has been highlighted. Even though it has been widely recognized that there are significant potentials in BIM by data sharing and reuse, BIM has not been actively utilized for building energy simulation. With this in mind, in this paper, the authors investigated several issues: (1) limitation of Industry Foundation Class (IFC) and BIM authoring tools, (2) immature IFC data schema, (3) data mapping problem between BIM and BEM. Firstly, IFC files exported from major BIM authoring tools are not consistent with each other and don't include significant thermal parameters. In addition, building geometry, e. g. underground wall, is not properly exported. IFC data schema are not ready to describe detailed information on thermal and dynamic properties (efficiency, performance curves, etc.) of mechanical systems (HVAC, AHU), delivery systems (fans, pumps), and plants (boilers, chillers), which are very essential for BEM. Finally, most of the efforts on BIM-to-BEM are focused on data conversion (data-driven approach), without considering dynamic architectural design process which involves many different stakeholders. In near future, BIM-to-BEM interface should take into account design context and rational decision making so called 'process-driven approach'.

BIM assisted Building Automation System information exchange using BACnet and IFC

Implementation of BIM + WebGIS Based on Extended IFC and Batched 3D Tiles Data: An Application in RCC Gravity Dam for Republication of Design Change Model

Holistic views of all environmental impacts for buildings such as Life Cycle Assessments (LCAs) are rarely performed. Building services are mostly included in this assessment only in a simplified way, which means that their embodied impacts are usually underestimated. Open Building Information Modeling (BIM) and Industry Foundation Classes (IFC) provide for significantly more efficient and comprehensive LCA performance. This study investigated how building services can be included in an open BIM-integrated whole-building LCA for the first time, identified challenges and showed six solution approaches. Based on the definition of 222 exchange requirements and their mapping with IFC, an example BIM model was modeled before the linking of 7312 BIM objects of building services with LCA data that were analyzed in an LCA tool. The results show that 94.5% of the BIM objects could only be linked by applying one of the six solution approaches. The main problems were due to: (1) modeling by a lack of standardization of attributes of BIM objects; (2) difficult machine readability of the building services LCA datasets as well as a general lack of these; and (3) non-standardized properties of building services and LCA specific dataset information in the IFC data format.

The Industry Foundation Classes (IFC) data model enables vendor-neutral data exchange across Building Information Modeling (BIM) processes. However, IFC has limitations in transferring underlying design logic, including geometric constraints between components and reference grids. The absence of grids hinders efficient IFC model reuse, especially when design modifications depend on them. To address these challenges, this paper introduces an automated method to enrich models with reference grids. Component positions are calculated from semantic and geometric model information, with a Genetic Algorithm (GA) applied to reduce unbound components and irregular grid spacing using numerical thresholds. The generated IfcGrid elements and dependencies are integrated into the IFC model to facilitate design modifications. The approach is demonstrated on eight models from different BIM tools, with its usability and efficiency validated through an expert survey. While refinement is needed for complex scenarios, the approach advances IFC enrichment and supports more efficient BIM workflows. • Grid enrichment by re-engineering spatial placement logic in design models. • Multi-threshold location alignment mechanism using IFC geometry and semantic attributes. • RRGA-based method providing designers with reference grids. • Streamlined workflow for converting IFC models into editable BIM models.