BIM–FM Interoperability Through Open Standards: A Critical Literature Review

Abstract

Interoperability between Building Information Modeling (BIM) and Facility Management (FM) depends on open, vendor-neutral standards. Yet, operational uptake remains constrained by fragmented workflows, incompatible schemas, and non-standardized delivery. This critical review synthesizes OpenBIM pathways—within the buildingSMART ecosystem (Industry Foundation Classes (IFC), Construction–Operations Building information exchange (COBie), Information Delivery Specification (IDS) v1.0, buildingSMART Data Dictionary (bSDD)) and the Level of Information Need (ISO 7817-1:2024)—across technical, managerial, and strategic dimensions. We searched major databases and used guided snowballing to screen a core corpus. Technically, persistent semantic inconsistencies and limited real-time, bidirectional exchange remain; open standards enable machine-checkable deliverables and API-friendly serializations. Managerially, weak Organizational Information Requirements (OIR) → Asset Information Requirements (AIR) → Exchange Information Requirements (EIR) alignment and unclear acceptance criteria undermine FM readiness. Strategically, procurement and risk management should mitigate vendor lock-in. We highlight gaps in FM ontologies and BIM–IoT synchronization and outline an agenda for Digital Twins, automation, and verifiable FM data quality within OpenBIM ecosystems.

1. Introduction

Among all building lifecycle phases, construction expenditure is concentrated within a short delivery window (≈2–3 years), whereas the Operation and Maintenance (O&M) phase spans several decades (commonly 40–60 years) and typically accounts for the majority of whole-life costs—often reported up to ~70% [1,2,3,4]. While Building Information Modeling (BIM) has enhanced collaboration and information flow during design and construction, its data often becomes underutilized or lost at the point of handover to Facility Management (FM) teams [5,6,7,8,9].

This disconnect has been referred to as the ‘value gap’—a misalignment between the as-built digital asset and the operational needs of FM. However, recent research suggests that this framing may overlook deeper systemic causes. A more explanatory lens is an incentive misalignment rooted in commercial and contractual frameworks, consistent with principal–agent theory [10]. Design and construction teams often lack motivation to deliver high-quality, FM-ready data, as the benefits are realized by downstream stakeholders [4,5]. This misalignment limits opportunities for optimizing operations and asset performance.

The problem is compounded by dependence on proprietary software, which raises long-term costs and limits interoperability. In addition, high technical barriers discourage FM participation and hinder adoption [11,12,13,14]. To address these challenges, the industry is shifting toward OpenBIM—a standards-based, non-proprietary approach using formats such as the Industry Foundation Classes (IFC) and Construction–Operations Building information exchange (COBie) [6,15,16]. These standards aim to support seamless, vendor-neutral data exchange, reduce information loss, and mitigate vendor lock-in—critical risks to long-term digital continuity [6,7,16,17,18].

Despite two decades of progress, BIM adoption in FM remains limited due to fragmented workflows, inconsistent data, and organizational resistance. These are not purely technical problems but multidimensional challenges that span technical, managerial, and strategic domains. This review addresses four research questions:

• How have technical approaches to OpenBIM-based BIM–FM interoperability evolved, and what limitations remain?
• What managerial processes and human factors affect data quality and information handover?
• What strategic drivers and barriers influence organizational investment in OpenBIM for FM?
• How do tensions across these dimensions shape future research directions?

To answer these questions, this article provides a critical review of the literature on BIM–FM interoperability through the lens of OpenBIM. It focuses on synthesizing key contributions, identifying recurring challenges and assumptions, and mapping gaps in both research and practice. The discussion is structured across technical, managerial, and strategic dimensions, providing an integrated perspective on barriers to OpenBIM adoption and suggesting directions for practical advancement.

2. Methodology

This review adopts a critical narrative (conceptual) synthesis to examine BIM–FM interoperability with a specific focus on open standards. A three-dimensional analytical framework—technical, managerial, and strategic—was developed to categorize and interpret key themes across the literature.

This framework is grounded in two foundational models commonly applied in digital transformation research:

• Socio-technical Systems Theory, which stresses the interdependence between technologies and the social systems in which they operate. It highlights the need to align tools with human roles, organizational structures, and culture to ensure effective implementation [19].
• The Technology–Organization–Environment (TOE) Framework, which conceptualizes adoption as influenced by three contexts: internal technology, organizational capacity, and the external environment [20].

Search strategy and screening. We queried Scopus and Web of Science (coverage to early 2025) using Title/Abstract/Keywords with Boolean strings such as: (“BIM” or “Building Information Modeling”) and (“facility management” or FM) and (“operation and maintenance” or O&M) and (interoperability). Initial retrieval: Scopus (n = 89) and Web of Science (n = 133), total = 222. After DOI/title deduplication, n = 221 unique records remained. Applying an OpenBIM eligibility filter (explicit reference to IFC, COBie, ISO 19650 [21], Level of Information Need, or IDS) yielded 28 core studies. Inclusion covered peer-reviewed articles, full conference papers, official standards/guidance, theses, and high-impact industry reports; trade press and non-scholarly sources were excluded.

Snowballing and conceptual framing. From the 28-record core set, we conducted backward/forward snowballing via Google Scholar to add foundational theory, standards (ISO, UK BIM Framework, buildingSMART), and policy/economic sources not comprehensively indexed in Scopus/WoS—supporting the socio-technical and TOE lenses.

Positioning. Although our workflow follows systematic steps (search–deduplicate–screen), this article is a critical narrative review that privileges depth and synthesis over exhaustive enumeration.

Each selected work was analyzed using the three-dimensional framework. Rather than aiming for exhaustive coverage, this review prioritizes depth over breadth, highlighting recurring technical barriers, organizational constraints, and strategic tensions—while also identifying where OpenBIM shows promise in bridging the gap between BIM and FM practice.

To enhance transparency and traceability, this review includes an exhaustive reference mapping table in Appendix A (

Table A1. Comprehensive Mapping of BIM–FM Interoperability References.

Theme	Topic	Implication	References
Semantic Enrichment	ifcOWL ontology for structured data	Formal logic, SPARQL query, compliance checking	[34,35]
	COBieOWL as extension of COBie	Enhances data expressiveness for FM delivery	[36]
	Modular domain ontologies for FM	Increased clarity and reusability	[17,51]
Semantic Enrichment (AI)	NLP/GNN to structure dark data	Unlocks unstructured logs, builds knowledge graph	[27,52]
Query and Access	IFC-graph/graph-based access	Improves querying and retrieval from IFC	[27]
Information Requirements	LoIN/IDS/bSDD data templates	Makes OIR/AIR/EIR explicit and machine-checkable	[25,32]
Smart IDM	Machine-readable IDM specifications	Structured, checkable delivery maps/process	[47,57,58]
IFC/COBie Limitations	Omission of geometry, inconsistent classification	Challenges for FM spatial reasoning	[22,25]
Real-time Exchange	ifcJSON, ifcXML via APIs	Improved web compatibility	[7,45,46,47,48]
Open Integration Layer	API-first + webhooks/message bus (MQTT)	Reduces lock-in; keeps BMS/CMMS in sync	[47,57,58]
IoT Semantics	BRICK schema and BMS tagging	Cross-domain semantic link to FM data	[45,55]
IoT Integration	MQTT, BACnet, O-MI/O-DF protocols	Feeds real-time sensor data into FM dashboards	[42,43]
IoT–BIM Fusion	Web-based DT with IFC + sensors	Three-dimensional spatial visualization of environmental data	[7,45]
GIS + BIM for FM	Integration of spatial/geographic info	Improved navigation, asset location accuracy	[46]
ISO 19650 Implementation	OIR/AIR misalignment	Need for clearer definition of FM-related info	[5,7,68]
ISO 19650 Visualization	Process modeling to simplify adoption	Graphical tools improve understanding	[62]
IFC for Maintenance	Inspection/maintenance representation in IFC	Native lifecycle attributes for FM tasks	[33]
Authoring-time Capture	Natural UIs for semantic enrichment	Practical duration of data capture	[38]
Data Governance	Data commissioning protocol	Improves accountability and handover quality	[67,68]
Digital Twins	DT of Performance vs. DT of Record	Real-time ops vs. lifecycle traceability	[43,53]
Economic Appraisal	LCC/TCO/CBA/EN 16627, NIST HB-135	Stronger, risk-aware business case	[74,75,77]
Change Management	Socio-technical roadmap (5 phases)	Aligns human–tech transformation	[71]
Organizational Barriers	FM teams lack BIM literacy	Requires training and leadership	[61,69,70]
Strategic ROI	Lifecycle value and risk mitigation	Beyond short-term cost focus	[5,72]
Public Policy	Mandates for IFC/COBie in procurement	Drives industry-wide adoption	[65]
Enterprise BIM	ISO 19650 within enterprise AM practice	Links standards to asset management	[63,65]
Digital Maturity Models	FM-DMM with 7 key dimensions	Enables benchmarking and progress tracking	[79]
Lifecycle Contracting	Aligning incentives across phases	Addresses the incentive gap	[5]

). This table categorizes reviewed works by theme, identifies their main topics and implications, and links each to the analytical dimensions used throughout this study. It complements the thematic synthesis in the main text and serves as a structured evidence base for the findings presented.

3. Dimensions of BIM–FM Interoperability Through Open Standards

Compared with earlier literature reviews that focused mainly on technical standards (e.g., IFC/COBie) or on general BIM adoption in the O&M phase, this review adopts a holistic, integrated lens. Prior studies such as Dixit and Abideen [9,18] offer valuable insights into BIM–FM integration but do not connect technical, managerial and strategic barriers within a single analytic frame. This study advances the discourse by introducing a structured three-dimensional framework; clarifying the incentive gap—an incentive misalignment in which costs are borne by upstream delivery teams while benefits accrue to downstream owners/FM stakeholders, consistent with principal–agent theory [4,5]; and synthesizing recent developments in semantic enrichment, digital maturity, and policy-based transformation, thereby providing a more actionable foundation for future research and practice.

3.1. Technical Dimension

The technical foundation of BIM–FM interoperability is built on open standards, particularly IFC and COBie. These standards aim to support structured and vendor-neutral data exchange across the building lifecycle [6,15,16]. However, persistent technical limitations continue to restrict their effectiveness in meeting real-world FM requirements.

3.1.1. Current State and Limitations of IFC and COBie

While IFC and COBie are widely adopted, both exhibit shortcomings that hinder efficient data use in FM. COBie’s lack of geometric data severely limits its suitability for spatial management and performance analysis, such as energy modeling [22,23]. IFC provides broader coverage, yet inconsistent schema implementation, classification errors across authoring tools, and uneven software support introduce semantic discrepancies that undermine reliable exchange [24,25,26]. Recent work also highlights query ability issues and proposes graph-based representations to improve access to IFC data [27].

As a result, FM teams frequently resort to manual enrichment and reconciliation to fill missing or mismatched information, which diminishes the efficiency of automated workflows [28,29]. Recent guidance converges on making information requirements explicit and checkable—using LoIN (ISO 7817-1:2024) [30], IDS v1.0, and client-led OIR/AIR/EIR development per the UK BIM Framework [31,32]. Further extensions include the following: extending IFC schemas for inspection/maintenance [33], adopting semantic web approaches such as ifcOWL and COBieOWL to increase clarity and interoperability [34,35,36,37], and developing interfaces that support practical semantic capture during authoring/commissioning [38]. Together, these lines of work move beyond earlier limitations by linking validation rules with semantic models, thereby reducing ad-hoc FM data fixes and improving trustworthy handover [25,27].

Ultimately, overcoming these technical limitations is not only a matter of expanding standards but also of enabling scalable, context-aware data interpretation—crucial for achieving reliable and automated BIM–FM integration. Rather than merely “expanding standards,” data quality improves when requirements are specified with the Level of Information Need (LoIN) (ISO 7817-1:2024) [30], encoded for automated checking via IDS v1.0 [31], and grounded in consistent property definitions using EN ISO 23386/23387 [39,40] (bSDD/data templates). This LoIN → IDS → bSDD pipeline reduces ambiguity and raises completeness and consistency at handover.

3.1.2. Bidirectional Data Exchange: APIs and Cloud Integration

Static exchanges using traditional IFC and COBie formats are insufficient for supporting real-time FM operations. These formats lack the responsiveness needed for continuous updates and dynamic system integration [41,42]. In contrast, modern Digital Twins (DTs) require ongoing, bidirectional data flow between BIM models and FM systems. This is increasingly achieved through RESTful APIs and open data formats that support seamless, low-latency communication [43,44]. The realities of vendor APIs are that major platforms expose REST APIs but often with proprietary payloads, rate/usage limits, and write restrictions. A practical mitigation is an open integration layer: normalize model data to IFC/ifcJSON, map operations telemetry via open schemas (e.g., BRICK/BACnet tags), and broker events with webhooks/message buses (e.g., MQTT). This keeps CMMS/BMS in sync without lock-in while allowing owners to retain data portability.

Emerging serializations such as ifcJSON and ifcXML improve web compatibility and can ease integration via APIs. However, performance and file size depend on use case and implementation; for file-based exchange, IFC-SPF (STEP) remains the most widely supported and typically most compact format. Evidence of speed/size benefits exists only in certain scenarios, not universally [7,45,46,47,48]. These formats support real-time use cases such as predictive maintenance and anomaly detection by enabling smooth integration with IoT data streams and AI algorithms [49,50].

Ultimately, API-driven interoperability is essential for transitioning from static data delivery to dynamic lifecycle intelligence. This shift enables faster decision-making, automated operations, and more resilient FM practices.

3.1.3. Semantic Enrichment and Linked Data

A key advancement in BIM–FM interoperability is the shift from static data exchange to dynamic, platform-based collaboration. This shift emphasizes composability—allowing organizations to integrate best-in-class tools through real-time, vendor-neutral APIs instead of relying on proprietary systems [6].

True interoperability requires more than syntactic compatibility; it depends on semantic coherence. Ontology-based approaches, such as ifcOWL, extend the expressiveness of IFC and enable structured querying, reasoning, and integration across domains [5,35]. While early work [34] demonstrated their potential, adoption remains limited due to complexity and performance concerns. Modular, domain-specific ontologies have been proposed to simplify implementation in FM contexts [51].

More recent approaches use artificial intelligence (AI) to automate semantic enrichment. Natural language processing (NLP) and graph neural networks (GNNs) can extract FM-relevant entities and relationships from unstructured data sources such as work orders and manuals—information often missing from IFC models. For example, BiLSTM-CRF models can identify items like equipment or locations in text and link them to BIM objects via knowledge graphs. GNN-based systems further enable natural language queries to be translated into formal query languages (e.g., BIMQL), enhancing usability for FM staff [27,52].

These techniques support the integration of structured and unstructured data into a unified semantic framework, enabling more intelligent, context-aware FM operations [53,54,55]. However, challenges remain in scalability, performance, and the lack of standardized semantic modeling tools.

3.1.4. Digital Twins: Integrating IoT, AR, and VR

DTs—virtual replicas of physical assets continuously updated through IoT data—are emerging as powerful tools for FM. They support real-time monitoring, predictive analytics, and immersive visualization, enabling better operational decision-making [41,43].

There are two conceptual types of DTs relevant to FM. The “Digital Twin of Performance” provides real-time insights into the current state of assets. In contrast, the “Digital Twin of Record” extends this by including historical, legal, and contextual information to support lifecycle planning and long-term accountability [53]. While the former is increasingly feasible with current technologies, the latter demands high data quality, governance protocols, and reliable traceability mechanisms.

DTs architectures rely on open standards such as IFC, IoT protocols like MQTT and BACnet, and web-based visualization tools including WebGL and three.js. These are often enhanced by immersive technologies such as augmented and virtual reality [38,56,57].

However, several barriers limit broader adoption. Semantic interoperability remains a key challenge, especially in integrating data across systems. In addition, issues related to data ownership, governance, and cybersecurity complicate deployment in operational contexts [5,58].

Addressing these issues requires coordinated progress in cross-domain data standards, semantic modeling frameworks, and analytics pipelines. Without these, the full potential of DTs as a backbone of intelligent FM cannot be realized.

3.2. The Managerial Dimension

While technical tools form the foundation of BIM–FM interoperability, their real-world success depends largely on effective management. Key factors include structured information governance, well-defined workflows, and alignment between technical processes and organizational roles [59,60,61]. In practice, the maturity of information management often plays a greater role in interoperability outcomes than technical sophistication alone.

3.2.1. Implementation Challenges of ISO 19650

As a global standard for lifecycle information management, the ISO 19650 series sets out concepts and processes for defining information requirements (e.g., OIR/AIR) and allocating roles, reviews, and acceptance criteria across the project team [32,62]. However, confusion frequently arises from the following: (i) overly general contractual requests and early contradictions in the first published version that leave key terms open to interpretation [63]; (ii) the translation gap between high-level owner purposes and detailed, checkable Exchange Information Requirements (EIRs) for multiple information receivers—an error-prone step when specificity is insufficient [32]; and (iii) unclear owner BIM-for-FM requirements, evidenced by thousands of handover compliance issues in multi-case field studies. Beyond drafting issues, socio-technical heterogeneity across stakeholders and toolchains also drives divergent interpretations in practice [63,64]. To make the standard actionable, recent work recommends ‘decoding’ ISO 19650 via process modeling to improve stakeholder communication and consistent execution [62].

In practice, OIR/AIR become operational when mapped to EIR with LoIN (ISO 7817-1:2024) [30] granularity and encoded in IDS, so deliverables can be machine-validated. This approach is already applied in the UK BIM Framework and by Nordic public owners (e.g., Statsbygg), which use machine validation (e.g., SIMBA) to check IFC models against requirement sets. We therefore reference these methods and tools (LoIN, IDS, and bSDD/EN ISO 23386/23387 [39,40] data templates) as concrete enablers of actionable workflows [31,32,65].

We distinguish fixable drafting issues (overly general contract wording, insufficient EIR specificity) from inherent socio-technical constraints (heterogeneous stakeholders, Common Data Environment (CDE), and toolchains); the former is addressable via process modeling, IDS/smart IDM, and semantic checks, whereas the latter requires governance and capability building alongside standardization.

To address these barriers, machine-readable specifications (e.g., buildingSMART IDS v1.0 and smart IDM) can express AIR/EIR (aligned with the LoIN and property templates per EN ISO 23386/23387/bSDD) explicitly and make them automatically checkable [31,66], while ontology-based representations (e.g., ifcOWL and COBieOWL) strengthen traceability and semantic validation across stages [35,36,54]. (By contrast, ifcJSON is a web-native serialization of IFC rather than an ontology.)

3.2.2. Ensuring Data Quality and Governance

Data quality remains a key challenge for BIM–FM interoperability, often compromised by incomplete or inconsistent asset handovers. Effective governance must combine proactive planning with technical validation. We frame this as data commissioning: a structured process that ensures FM data are defined, validated and accepted before closeout [64,67]. Inspired by physical commissioning, data commissioning entails three steps: (1) a Data Handover Specification that expresses AIR/EIR in a machine-readable form (e.g., buildingSMART IDS v1.0); (2) automated rule-based checks (e.g., Solibri) on IFC/COBie deliverables to verify compliance; and (3) formal acceptance by FM stakeholders, recorded in the CDE. This procedure improves accountability and reduces rework, making digital deliverables usable from day one of operations [31,66]. Semantic/ontology-based validation (e.g., ifcOWL and COBieOWL) further supports automated checks and cross-disciplinary traceability [35,36,55]. Importantly, this reframes high-quality FM data as a contractual deliverable, addressing the incentive misalignment that often undermines FM-readiness [64].

FM priorities. (1) Commission data at closeout—publish a Data Handover Specification, express AIR/EIR as IDS, validate IFC/COBie, and record FM sign-off in the CDE; (2) align OIR → AIR → EIR with LoIN so each FM use case has the right granularity at each milestone; (3) adopt open, API-first integration (IFC/COBie/ifcJSON) to sync BMS/IoT/CMMS; (4) embed automated conformance checks (IDS/QA rules) to reduce manual enrichment; (5) evaluate the organization’s assess baseline FM digital maturity and track lifecycle KPIs (e.g., work-order cycle time and data completeness at acceptance).

Handover acceptance checks. Critical system asset coverage ≥ 95%; all mandatory LoIN fields complete (per IDS); validation errors ≤ 1% (IDS/Solibri logs); zero orphan spaces/zones; CMMS import passes (no blocking errors).

Common failure modes → fixes.

COBie import fails → normalize naming, deduplicate keys, pre-check with IDS.

IFC–CMMS mismatch (missing Pset_) → apply LoIN-driven property templates and re-validate via IDS.

IoT/BMS tags not linkable → define a point-ID convention (e.g., BRICK) and write IDs back to IFC/CMMS [55,68].

3.2.3. Overcoming Human and Organizational Barriers

Achieving BIM–FM interoperability requires more than technical upgrades—it demands alignment between technology, people, and organizational culture. Common barriers include limited BIM literacy among FM professionals, unclear role definitions, and resistance to process change [61,69,70]. To address these challenges, researchers emphasize the importance of integrated change management that combines technical training with organizational transformation. Refs. [68,71] propose a five-phase roadmap for managing this transition (in this paper, a “5-phase model” denotes a five-step organizational roadmap for BIM-enabled FM—team formation, vision/KPIs, targeted pilots, training/monitoring, and institutionalization—adapted from recent change-management literature [71]):

• Assemble a multidisciplinary change team (deliverable: named information roles/owners).
• Define a clear vision and performance indicators (KPIs) (deliverable: KPI set aligned to FM use cases).
• Launch pilot projects to test new workflows (deliverable: BEP annex + Data Handover Specification draft).
• Provide training and monitor adoption (deliverable: training completion and usage metrics in the CDE).
• Reinforce change through ongoing leadership and realized benefits (deliverable: formal FM sign-off criteria and continuous improvement cycle).

The training stream explicitly prepares FM staff to run IDS checks, interpret validation logs, update asset records in the CDE, and perform CMMS import/verification—linking learning to day-to-day FM tasks.

This approach highlights that BIM–FM integration is not a one-time software deployment but a long-term strategic initiative that requires cultural buy-in and leadership commitment across the organization.

3.3. Strategic Dimension

Strategic adoption of OpenBIM can reduce vendor lock-in, ensure long-term data accessibility, and drive digital transformation across the built environment. However, its return on investment (ROI) is often difficult to quantify due to intangible FM benefits such as better collaboration, improved decision-making, and risk reduction. As a result, scholars recommend shifting from a cost-saving focus to a risk-based valuation approach. This reframes BIM as infrastructure for minimizing risks—including regulatory penalties, operational disruptions, and data inaccessibility—rather than as a tool for short-term savings [5,55,72].

Brief acknowledgement of the economic perspective. Beyond generic ROI arguments, recognized economic appraisal methods strengthen the business case. Life-Cycle Costing (LCC) provides the formal whole-life view of digital and operational expenditures and should frame option selection (ISO 15686-5) [73]; Total Cost of Ownership (TCO) can serve as a managerial shorthand when anchored in LCC assumptions and sensitivity testing [25,54,74]. In public or regulated contexts, Cost–Benefit Analysis (CBA) complements LCC by capturing monetized and non-monetized benefits (e.g., avoided downtime and compliance risk) [75], while energy-related measures follow Life-Cycle Cost Analysis (LCCA) conventions [76]; European settings may also reference EN 16627 for consistent reporting [77]. This encourages viewing OpenBIM not as an optional upgrade but as a strategic asset for resilience and accountability.

The Technology–Organization–Environment (TOE) Framework further clarifies how OpenBIM success depends on three interrelated factors: technological capability (e.g., APIs and IfcJSON), organizational readiness (e.g., leadership and governance), and external pressures (e.g., regulations and client demands) [6,61]. In practice, TOE becomes actionable when economic appraisal is embedded into organizational readiness—e.g., LCC-based option ranking with defined analysis periods and discount rates, budget lines for information management (CDE, model upkeep, validation, API maintenance), and KPI tracking within FM management systems (ISO 41001) [78].

Government mandates play a critical role in accelerating OpenBIM adoption. When aligned with ISO 19650 and national digital strategies, public procurement requirements—such as the mandatory use of IFC and COBie—can stimulate industry-wide standardization and innovation [65,67,69]. These mandates often create a “trickle-down” effect, where private firms adopt OpenBIM practices by default, raising overall ecosystem maturity.

Assessing Organizational Readiness via Digital Maturity Models

To scale OpenBIM adoption beyond pilot projects, organizations must evaluate their internal capabilities. The FM Digital Maturity Model (FM-DMM) offers a structured approach by assessing seven key areas: Strategy and Leadership, Organization, Technology, Data Management, People, Process, and Client-centricity. These dimensions align closely with the technical, managerial, and strategic requirements of BIM–FM interoperability [79]. Applying such models enables targeted improvement, benchmarking, and long-term capability development.

4. Synthesis of Challenges and Future Research Directions

Despite increased academic and industry interest in OpenBIM-based BIM–FM interoperability, full-scale implementation remains limited. These challenges are multidimensional—technical, managerial, and strategic—and are deeply interconnected. As illustrated in Figure 1, each dimension contributes distinct functions within a layered ecosystem. Their vertical alignment—from raw data to knowledge and ultimately decision-making—is essential to transform BIM data into operational intelligence.

4.1. Technical Gaps

• Scalability of Semantic Tools: Ontology-based frameworks like ifcOWL are promising but face complexity and performance issues at scale.
• Lack of Modular Ontologies: FM-specific ontologies that are both reusable and easy to implement are still underdeveloped.
• Limited Real-Time Integration: Bidirectional, dynamic BIM–FM synchronization remains rare despite the availability of APIs.
• Weak AI Integration: Semantic BIM data is not yet fully leveraged for predictive maintenance or fault detection.

Suggested Future Directions: Research should prioritize lightweight, modular ontologies, real-time RDF/SPARQL pipelines, and hybrid BIM–IoT–AI architectures to support scalable FM automation.

Implementation challenges and mitigations. We pair each proposed solution with likely constraints and remedies: LoIN/IDS/bSDD—authoring and governance overhead → reusable rule libraries and data commissioning with CDE-based acceptance; ontology-based checks—complexity/performance at scale → modular FM ontologies and targeted use cases; API-driven integration—rate limits and proprietary payloads → an open integration layer that normalizes IFC/ifcJSON, maps telemetry via BRICK/BACnet tags, and brokers events through webhooks/MQTT; change management—capability gaps and resistance → phased training, KPIs and institutionalization.

4.2. Managerial Gaps

• OIR–AIR Misalignment: Poor linkage between high-level organizational goals and asset-level data leads to ineffective handovers.
• Unclear Roles and Weak Governance: Fragmented workflows and unclear accountability compromise data quality.
• Low BIM Literacy: Resistance to change and skill gaps among FM staff slow adoption.

Suggested Future Directions: Future studies should explore co-created AIR frameworks, stakeholder-driven design methods, and evaluate the role of BEPs in FM-phase governance.

4.3. Strategic Gaps

• Unclear ROI: While OpenBIM is seen as beneficial long-term, few studies quantify its impact in measurable terms.
• Understudied Policy Effects: The influence of national mandates on FM digital readiness is not well documented.
• Lack of Maturity Models: There is no widely accepted model to benchmark digital readiness for OpenBIM in FM.

Suggested Future Directions: Research should develop OpenBIM maturity benchmarks and lifecycle-aligned KPIs and evaluate the impact of policy instruments on FM transformation. To consolidate these thematic gaps,

Table 1. Matrix of Future Research Directions for Advancing BIM–FM Interoperability.

Dimension	Research Focus	Proposed Action	Intended Impact
Technical	Hybrid Semantic Frameworks	Combine ontologies (e.g., ifcOWL) with AI/NLP techniques	Enable scalable, machine-readable BIM–FM integration
	Digital Twin Architectures	Integrate DTs with version control (e.g., blockchain)	Provide legally reliable “DTs of Record”
Managerial	Validation of Change Roadmaps	Conduct longitudinal case studies using 5-phase models	Offer evidence-based transformation strategies
	Data Commissioning Protocols	Define specs, validation steps, and sign-off workflows	Make FM-ready data a contractually enforceable output
Strategic	Lifecycle-Aware Contracting	Link BIM deliverables to FM incentives and outcomes	Align cross-phase stakeholder accountability
	Policy Impact Measurement	Compare digital maturity across mandated/non-mandated cases	Guide effective national and sectoral policy design
	FM-DMM Benchmarking	Validate maturity models across sectors *	Provide sector-specific digital readiness baselines

* Cross-sector validation: healthcare (hospitals), higher-education campuses, transportation hubs (airports/rail), public-sector offices, industrial/data centers, hospitality/retail portfolios, and social housing. Validation entails benchmarking FM-DMM scores and common FM KPIs (e.g., asset uptime, work-order cycle time, and data completeness at acceptance) to produce sector-specific digital-readiness baselines [79].

presents a structured matrix linking research domains with recommended actions and intended outcomes.

5. Contributions and Stakeholder Implications

This review synthesizes fragmented scholarship into a structured lens for BIM–FM interoperability and links the synthesis to actionable steps for practice and policy seen

Table 2. Stakeholder Implications for BIM–FM Interoperability.

Stakeholder	Key Implication	Suggested Action
Facility Owners and Operators	Treat FM data as a contractual deliverable, not a passive handover	Define a Data Handover Specification; express AIR/EIR as IDS; implement data commissioning (acceptance criteria, tests, sign-off); assess FM digital maturity
Project Managers and BIM Coordinators	Early alignment between OIR–AIR–EIR is critical to downstream interoperability	Co-develop AIR with FM; include BEP annex for data handover; run rule-based checks on IFC/COBie before closeout; assign information roles
FM Professionals	Usability remains a barrier	BIM-for-FM curriculum: (1) IFC/COBie for FM; (2) LoIN/IDS authoring and reading validation logs; (3) CDE workflows and issue tracking; (4) QA/QC with Solibri/IDS; (5) CMMS field mapping; (6) basics of API/webhooks for ops data
Software Developers/Vendors	Closed platforms hinder integration	Ship API-first with openness: IFC/COBie/ifcJSON round-trip; published quotas and event webhooks; IDS validation endpoints and BRICK/ontology options; export without proprietary bindings
Policymakers and Regulators	Tie mandates to outcomes, not formats alone	Require interoperable, auditable deliverables (IFC/COBie/IDS) in procurement; incentivize lifecycle performance and data quality

.

• Integrated lens: Organizes evidence across technical, managerial, and strategic dimensions to clarify how data, processes, and stakeholders interact over the lifecycle.
• Implementation insights: Identifies specific ISO 19650 pain points (contract wording, EIR specificity, handover compliance) and proposes governance remedies (data commissioning, machine-readable AIR/EIR via IDS/smart IDM, ontology-based validation).
• Gap agenda: Maps research and practice gaps (FM-aligned ontologies, NL interfaces, outcome-based contracting, maturity benchmarking, policy evaluation).

Translate these contributions into concrete actions for owners, delivery teams, vendors, and policymakers.

6. Conclusions

This review has explored the complex challenges and emerging opportunities in achieving BIM–FM interoperability through open standards. By categorizing findings across technical, managerial, and strategic dimensions, it offers a structured understanding of how data, processes, and stakeholder ecosystems interconnect across the building lifecycle.

• Technically, while standards such as IFC and COBie provide a foundation for data exchange, they face limitations in semantic richness, real-time integration, and AI readiness. Advances in web-native formats, semantic web technologies, and AI-driven knowledge graphs offer more scalable and context-aware data ecosystems.
• Managerially, issues such as unclear information requirements, absence of data commissioning, and resistance to change continue to hinder adoption.
• Strategically, quantifying ROI remains difficult, and the lack of lifecycle-based policy incentives limits broader implementation.

For practitioners and digital transformation leaders, this review offers a practical roadmap. Key actions include adopting open data standards and APIs, implementing change management strategies, and applying FM-specific digital maturity models for benchmarking. Policymakers can further support progress by introducing mandates that incentivize high-quality, interoperable data delivery.

Limitations. This review is a conceptual synthesis rather than a registered systematic review. We did not conduct a formal study quality or risk-of-bias appraisal, and heterogeneity precluded meta-analysis. Accordingly, the conclusions are directional rather than exhaustive and should be triangulated in future work with gray literature, multilingual searches, and primary field studies.

Future advancements will require the co-evolution of semantic tools, Digital Twins, governance frameworks, and incentive structures. Bridging persistent gaps—between theory and implementation, standards and context, data and value—is essential to scale up from prototype systems to integrated, intelligent FM operations.

As buildings become increasingly data-rich and interconnected, the future of BIM–FM interoperability lies in real-time, semantically aligned, and lifecycle-integrated ecosystems. Rather than static handovers, FM will rely on dynamic Digital Twins, AI-assisted reasoning, and open, API-first infrastructures enabling continuous feedback across design, construction, operations, and policy layers.

To realize this vision, future research should address the following:

• Develop interoperable ontologies that are lightweight, modular, and FM-aligned.
• Integrate natural language interfaces to reduce technical barriers for FM professionals.
• Explore contractual models that reward data quality and lifecycle value delivery.
• Advance cross-sector digital maturity models for benchmarking and planning.
• Evaluate the long-term impacts of policy mandates, not only on compliance but also on innovation and organizational learning.

Ultimately, the transition from fragmented data exchange to operational intelligence will require not only technical innovation but also stronger alignment between human, organizational, and regulatory systems.