TY - GEN
T1 - AEC Digital Twin Data - Why Structure Matters
AU - Borrmann, André
AU - Schlenger, Jonas
AU - Bus, Nicolas
AU - Sacks, Rafael
N1 - Publisher Copyright:
© 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Data Model
KW - Digital Twin
KW - Information Model
KW - Object-oriented Modeling
KW - Ontology
UR - http://www.scopus.com/inward/record.url?scp=85174742994&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-35399-4_46
DO - 10.1007/978-3-031-35399-4_46
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AN - SCOPUS:85174742994
SN - 9783031353987
T3 - Lecture Notes in Civil Engineering
SP - 651
EP - 669
BT - Advances in Information Technology in Civil and Building Engineering - Proceedings of ICCCBE 2022 - Volume 1
A2 - Skatulla, Sebastian
A2 - Beushausen, Hans
T2 - 19th International Conference on Computing in Civil and Building Engineering, ICCCBE 2022
Y2 - 26 October 2022 through 28 October 2022
ER -