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AEC Digital Twin Data - Why Structure Matters

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Advances in Information Technology in Civil and Building Engineering (ICCCBE 2022)

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 357))

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Abstract

With the increasing adoption of the Digital Twin concept in the construction industry in the operations and maintenance phase, researchers and practitioners are increasingly seeking suitable technological solutions for the design and construction phases. While it is widely accepted that the required platforms hosting the digital twin must be cloud-based to fulfill the requirements of ubiquitous accessibility and centralized consistency, questions regarding the need for data schema remain. Some academics argue that a structure-free organization of data is suitable for realizing digital twins and the data streams from and to the respective platform. Hands-on experience in the BIM2TWIN project supports a counter argument, i.e., that structure-free data is insufficient for most use cases around AEC Digital Twins. The sheer information complexity of construction projects requires well-defined data structures enabling unambiguous and error-less interpretation. This becomes apparent when reflecting on the well-established concept of the data-information-knowledge pyramid describing that raw data must be processed into understandable and meaningful high-level information for human decision makers, subsequently providing the basis for cross-project domain knowledge. Based on this observation, we highlight that object-oriented modeling is a widely recognized information modeling technique that facilitates the structuring of complex domain information. We compare it with ontology-based model concepts that provide a similar, yet more abstract means for information modeling.

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Notes

  1. 1.

    https://bim2twin.eu/.

  2. 2.

    https://hellofuture.orange.com/en/thingin-the-things-graph-platform/.

  3. 3.

    https://www.arangodb.com/.

  4. 4.

    E.g. https://opendatabim.io/.

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Acknowledgements

The research presented in this paper has been partially funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 958398, “BIM2TWIN: Optimal Construction Management & Production Control”, as well as Transregio 277 “Additive Manufacturing in Construction – The Challenge of Large Scale” funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - project number 414265976 - TRR277.

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Authors and Affiliations

  1. Chair of Computational Modeling and Simulation, Technical University of Munich, Munich, Germany

    André Borrmann & Jonas Schlenger

  2. Centre Scientifique et Technique du Bâtiment, Sophia-Antipolis, France

    Nicolas Bus

  3. Technion – Israel Institute of Technology, Haifa, Israel

    Rafael Sacks

Authors
  1. André Borrmann
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  2. Jonas Schlenger
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  3. Nicolas Bus
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  4. Rafael Sacks
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Corresponding author

Correspondence to André Borrmann .

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Editors and Affiliations

  1. Department of Civil Engineering, University of Cape Town, Rondebosch, South Africa

    Sebastian Skatulla

  2. Department of Civil Engineering, University of Cape Town, Rondebosch, South Africa

    Hans Beushausen

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Borrmann, A., Schlenger, J., Bus, N., Sacks, R. (2024). AEC Digital Twin Data - Why Structure Matters. In: Skatulla, S., Beushausen, H. (eds) Advances in Information Technology in Civil and Building Engineering. ICCCBE 2022. Lecture Notes in Civil Engineering, vol 357. Springer, Cham. https://doi.org/10.1007/978-3-031-35399-4_46

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  • DOI: https://doi.org/10.1007/978-3-031-35399-4_46

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  • Print ISBN: 978-3-031-35398-7

  • Online ISBN: 978-3-031-35399-4

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