A linked-data paradigm for the integration of static and dynamic building data in digital twins

Mavrokapnidis, Dimitris; Katsigarakis, Kyriakos; Pauwels, Pieter; Petrova, Ekaterina Aleksandrova; Korolija, Ivan; Rovas, Dimitrios

doi:10.1145/3486611.3491125

Cited by 15 publications

(9 citation statements)

References 8 publications

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“…Effective information management for built assets needs to deal with several challenges, among which data integration of heterogeneous data from autonomous sources is an important premise for follow-up data analysis and decision-making. In accordance with the IMF defined by Hetherington and West [7], this paper proposes a candidate Foundation Data Model (FDM) by merging the BOT and BRICK ontologies in OWL, which can complementarily represent building topologies and MEP facilities [15]. Of course, this is not the only choice.…”

Section: Methodsmentioning

confidence: 99%

Enabling building digital twin: Ontology-based information management framework for multi-source data integration

Xie

Moretti

Merino

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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The emergence of the digital twin concept can potentially change the way people manage built assets thoroughly. This is because the semantics-based model and linked data approach behind the digital twin, as the successor of classical BIM, provide strong capability in integrating data from fragmented and heterogeneous sources and thus enable better-informed decision-making. Taking buildings as the case, this paper demonstrates the ontology-based Information Management Framework and elaborates on the process to integrate data through a common data model. Specifically, the Foundation Data Model (FDM) representing the operation of buildings and embedded systems is developed and two patterns of integration architecture are compared. To conceptualise all the essential entities and relationships, the building topology ontology and BRICK ontology are reused and merged to serve as a feasible FDM. According to the characteristic of asset management services that digital twins support, two integration architectures are compared, including the data warehouse approach and the mediator approach. A case study is presented to elaborate on the implementation of these two approaches and their applicability. This work sets out the standardised and modularised paradigms for discovering, fetching, and integrating data from disparate sources with different data curation manners.

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Section: Methodsmentioning

confidence: 99%

Enabling building digital twin: Ontology-based information management framework for multi-source data integration

Xie

Moretti

Merino

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…Due to this limited understanding of the intricate nature of this technology, companies may be hesitant to invest in DT platforms or allocate resources for personnel training. As well as apprehensions regarding the integration of emerging technology into existing systems or concerns regarding potential disruptions during the transition phase have contributed to the barriers to DT adoption (Mavrokapnidis et al 2021).…”

Section: Operation and Maintenance Phasementioning

confidence: 99%

A review of drivers and barriers of Digital Twin adoption in building project development processes

Jahangir,

Schultz,

Kamari

2024

ITcon

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Over the past few years, the AECO Industry has undergone a shift toward digital transformation, with a growing trend towards adopting innovative technologies such as Digital Twin (DT). DT offers a wide range of applications throughout the building development process. However, some specific factors impede its widespread adoption in the building industry. This study aims to systematically review the available literature on the building project development process from the perspective of DT, with a particular focus on predictive simulations, i.e., co-sims. The review provides a comprehensive overview of drivers and barriers to DT adoption through an analysis of 147 studies between 2013 and 2023. The research identifies seven external and 41 internal drivers, including efficient project management and monitoring, predictive maintenance, and the collection and visualization of real-time data, all of which contribute to improved decision-making processes and reduced operational expenses. Further, the study identifies nine external and 31 internal barriers that impede the adoption of DT in the building development process. These barriers encompass challenges such as a high initial investment cost, a scarcity of a skilled workforce, difficulties in data interoperability, and resistance to change within the organization. A key outcome of the literature review is having identified the opportunity to exploit technologies developed in the automotive sector that enable a seamless integration of specialized simulator models in building development processes, resulting in collaborative simulations. Thus, we propose the concept of a Building Simulation Identity Card (BSIC) to be pursued in future research that would enable stakeholders to address the challenges of collaboration, cooperation, coordination, and communication by creating a common vocabulary to effectively facilitate the adoption of DT in the building's development process.

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“…• Enrich the graph with missing information us- As a first step, information about the HVAC system topology (i.e. HVAC, Spatial components and their relationships) is extracted both from architectural (ARC) and MEP IFC models, using an extended version of the Knowledge Graph Generator (KGG) 1 tool developed by Mavrokapnidis et al (2021). This tool is available online 2 .…”

Section: Proposed Workflowmentioning

confidence: 99%

Semi-automated extraction of HVAC system topology from imperfect Building Information Models

Mavrokapnidis,

Lilis,

Katsigarakis

et al. 2023

Building Simulation Conference Proceedings

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Knowledge of the HVAC system topology is required in several design and operation activities, including setting up building energy simulation models, fault detection and control applications, and facility management tasks. In theory, we can use the geometric context captured in Building Information Models (BIM) to infer these topological relationships; in practice, these models are far from perfect, with modelling errors and omissions. The implication is that manual remodelling is required, which results in unnecessary and redundant work. This paper discusses first the data quality issues faced in real-world data transformation workflows. We propose a methodology for generating good-quality HVAC topological models from imperfect BIM models. Our method's core is a rule-based model-checking framework to identify missing elements. Once an issue is detected, a geometric-relationship enrichment tool is invoked to infer missing topological information. The proposed approach is tested in a real-world complex BIM model, and we discuss lessons learnt. Highlights• Used ontologies of the building domain to represent HVAC system topological information. • Developed a rule-based model checking mechanism to identify missing relationships. • Used geometric processing to enrich the models with such information.

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A linked-data paradigm for the integration of static and dynamic building data in digital twins

Cited by 15 publications

References 8 publications

Enabling building digital twin: Ontology-based information management framework for multi-source data integration

Enabling building digital twin: Ontology-based information management framework for multi-source data integration

A review of drivers and barriers of Digital Twin adoption in building project development processes

Semi-automated extraction of HVAC system topology from imperfect Building Information Models

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