Civil Infrastructure Digital Twins: Multi-Level Knowledge Map, Research Gaps, and Future Directions
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Digital Twins (DTs) have received considerable attention as an emerging technology in recent years, which can offer advantages for improving the performance of infrastructures. However, the inherent complexity of infrastructures alongside the nascent nature of digital twins in the Architecture, Engineering, and Construction (AEC) industry hinders the adoption of infrastructure digital twins (IDTs). The lack of common understanding among different stakeholders has been noted as one of the most significant roadblocks to implementing IDTs in practice. This study is a quantitative attempt to address this gap by providing different stakeholders with a multi-layer knowledge map by analyzing 139 identified IDTs in three levels of bibliometric and social network analyses. First, knowledge themes are extracted from the most-frequent journals to provide an overview of IDT knowledge. Second, a combination of co-citation analysis and social network theories illustrated six clusters of IDT knowledge and their relationships. Third, the co-occurrence network of keywords revealed where, why, and what enabling technologies have been employed so far. These findings were synthesized into a three-layer knowledge map to not only illustrate the maturity level and evolution potentials of each layer but also serve as a hierarchical strategic plan recommending future direction to decision-makers, researchers, and practitioners.
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Naderi and Shojaei (2022) identified research gaps in digital twin adoption for infrastructure.
“Identifies research gaps in digital twin adoption for infrastructure”
From Advancing civil infrastructure with digital twins: a review of applications and challenges (2025) · cites this paper as Naderi and Shojaei (2022)
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Nhamage, I. A., Horas, C. S., Dang, N.-S., Matos, J. C., & Martins, J. P. (2025) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-025-10280-1 · Cited by 18 · see citing works
Developing a BIM Single Source of Truth Prototype Using Blockchain Technology
Hijazi, A. A., Perera, S., Alashwal, A. M., & Calheiros, R. N. (2022) · Buildings · doi:10.3390/buildings13010091 · Cited by 16 · see citing works
Digital twin non-fungible token (DT-NFT): Enabling data ownership in the AEC industry
Naderi, H., & Shojaei, A. (2024) · Automation in Construction · doi:10.1016/j.autcon.2024.105777 · Cited by 14 · see citing works
Self-citationYu, G., Ju, R., Sugumaran, V., & Liu, H. (2025) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2025.111973 · Cited by 14 · see citing works
Huang, J., Wu, P., Li, W., Zhang, J., & Xu, Y. (2024) · Structural durability & health monitoring · doi:10.32604/sdhm.2024.050338 · Cited by 13 · see citing works
Chen, Y., & Ding, C. (2023) · Architectural Engineering and Design Management · doi:10.1080/17452007.2023.2291585 · Cited by 11 · see citing works
Advancing civil infrastructure with digital twins: a review of applications and challenges
Kaveh, H., & Alhajj, R. (2025) · Journal of Civil Engineering and Management · doi:10.3846/jcem.2025.24921 · Cited by 12 · see citing works
Wang, Y., Rezaei, A., & Hicks, S. (2026) · Journal of Information Technology in Construction · doi:10.36680/j.itcon.2026.007 · Cited by 12 · see citing works
Solmaz, A. Ş. (2025) · Journal of Innovative Engineering and Natural Science · doi:10.61112/jiens.1572660 · Cited by 5 · see citing works
Digital twin applications in geotechnical engineering: a systematic review
Wang, Y., Rezaei, A., & Hicks, S. (2025) · Machine Learning and Data Science in Geotechnics · doi:10.1108/mlag-02-2025-0005 · Cited by 8 · see citing works
Determining Decision-Making Factors for Technology Adoption in the Construction Industry
Hatoum, M. B., & Nassereddine, H. (2024) · Artificial intelligence · doi:10.5772/intechopen.1004365 · Cited by 5 · see citing works
Dijital ikiz üzerine yapılan araştırmaların dergi yayınlarındaki eğilimlerinin görselleştirilmesi
ALPTEKİN, G., & TÜRKMEN, D. (2023) · Açıköğretim Uygulamaları ve Araştırmaları Dergisi · doi:10.51948/auad.1309385 · Cited by 5 · see citing works
Naderi, H., Ly, R., & Shojaei, A. (2024) · Construction Research Congress 2024 · doi:10.1061/9780784485262.031 · Cited by 7 · see citing works
Self-citationNaderi, H., Shojaei, A., & Heydari, M. H. (2025) · Journal of Information Technology in Construction · doi:10.36680/j.itcon.2025.007 · Cited by 3 · see citing works
Self-citationStructural design and construction using energy analytical modelling for sustainability: a review
(2024) · International Journal of Advanced Technology and Engineering Exploration · doi:10.19101/ijatee.2023.10102084 · Cited by 2 · see citing works
Alexandridis, K., & LaFontaine, M. (2024) · Springer eBooks · doi:10.1007/978-3-031-67778-6_10 · Cited by 1 · see citing works
Assessing the Scholarly Landscape: A Bibliometric Journey through Credit Rating Agency Research
Shafna.T, E. K. S. (2023) · European Economic Letters (EEL) · doi:10.52783/eel.v13i5.960
Fundamentals of computer science for infrastructure management
Wang, H., Zaheer, Q., Qiu, S., Malik, M., Peng, J., Naeem, M., Ehsan, H., & Shah, S. M. A. H. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-34017-8.00002-8
Zhang, A. A., Zaheer, Q., Qiu, S., Wang, W., Shah, S. M. A. H., Wang, J., Cui, D., Li, Z., & Shah, S. F. H. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-34017-8.00010-7
A Review of Digital Twins in Smart Environments
Kissiouer, I. B., Ouchani, S., & Bouarfa, H. (2025) · International Conference on Intelligent Computer Systems, Data Science and Applications (IC2SDA) · doi:10.1109/ic2sda68097.2025.11331414
Digital twin maturity in the built environment: A systematic review of 112 implementation cases
Zhu, N., Tezel, A., Fang, Z., Palihakkara, A. D., Tokbolat, S., Osorio-Sandoval, C. A., Wang, F., & Airey, G. D. (2026) · Advanced Engineering Informatics · doi:10.1016/j.aei.2026.105018
Digital twins and AI in civil engineering: a sustainability review from Colombia
Pradilla, M. M. S., Castellanos, N. T., Guevara, E. H., & Torres, K. T. (2026) · Proceedings of the Institution of Civil Engineers - Engineering Sustainability · doi:10.1680/jensu.25.00218
Jin, H., Zhou, S.-M., Chen, H., Xie, Z., Li, F., Li, Y., Zhu, J., Ling, Y.-F., Wu, Z., & Zhou, X. (2026) · Engineering Structures · doi:10.1016/j.engstruct.2026.123697
Ahmed, S., Zainordin, N. B., & Arof, K. Z. M. (2026) · Buildings · doi:10.3390/buildings16204017
- Authors
- Naderi, H., & Shojaei, A.
- Affiliations
- Virginia Tech (US)
- Venue
- IEEE Access
- Published
- 2022
- Volume
- 10
- Pages
- 122022-122037
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W4312858553
- Cited by
- 31
- References
- 105
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 8 · 2023: 6 · 2022: 2
- FWCI
- 2.84
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Virginia Polytechnic Institute and State University
- Topics
- Physical Sciences › Engineering › Building and Construction › BIM and Construction Integration
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Keywords
- civil infrastructure, knowledge maps, stakeholder knowledge, research gaps, AEC industry, technology adoption, knowledge evolution, enabling technologies, co-citation analysis, keyword co-occurrence network
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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