The DOI matches its Crossref record; 22 of the 23 references it cites were found in a registry or an index.
Digital Twins of the Ocean can foster a sustainable blue economy in a protected marine environment
Open accessAbstract
While the field of hydrography is crucial for maritime navigation and other maritime applications, oceanography is the field that provides the relevant data and knowledge for predicting climate change, monitoring marine resources, and exploring marine life. Digital ocean twins combine these two exciting fields and combine ocean observations and ocean models to establish virtual representations of a real world system, in this case the ocean or an ocean area, as well as assets in the ocean and processes within ocean industries or the natural environment. They have the potential to play a critical role in optimising and supporting sustainable ocean development. Digital Twins are synchronised with their real-world counterparts at a specific frequency and fidelity. They can provide valuable insights into the ocean's state and its evolution over time, which can be used to support decision-making in ocean governance and various ocean-related industries. Digital ocean twins can transform human ocean interactions by accelerating holistic understanding, optimal decision-making, and effective interventions. Digital twins of the ocean use ocean observations, historical and forecast data to represent the past and present and simulate possible future scenarios. They are motivated by outcomes, tailored to use cases, powered by integration, built on data, guided by domain knowledge, and implemented in IT systems. In this article, we explore the benefits of digital twins for the ocean, the challenges in developing them, and the current state of the art in ocean digital twin technology. One of the main benefits of digital ocean twins is their ability to provide accurate predictions of ocean conditions under expected interventions. Their information can be used to support decision- making in various applications including ocean-related industries, such as fishing, shipping, and offshore energy production. Additionally, digital twins can help to improve our understanding of the ocean's complex processes and their interactions with human activities, such as climate change, pollution, resource extraction and overfishing. Researchers and IT companies are combining various technologies and data sources, such as the Internet of Things for ocean observations, state of the art data science, artificial intelligence and machine learning, data spaces and vocabularies into digital ocean twins to contextualise data, improve the accuracy of ocean models and make ocean knowledge more accessible to a wide range of users.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The text we found for this paper looks like another document, so the self-check wasn’t run.
Citations
Cites
Grubler, A., Wilson, C., Bento, N., Boza-Kiss, B., Krey, V., McCollum, D. L., Rao, N. D., Riahi, K., Rogelj, J., De Stercke, S., et al. (2018) · Nature Energy · doi:10.1038/s41560-018-0172-6 · Cited by 1,178
Talley, L. D. (2013) · Oceanography · doi:10.5670/oceanog.2013.07 · Cited by 943
Review of the current status, technology and future trends of offshore wind farms
Díaz, H., & Soares, C. G. (2020) · Ocean Engineering · doi:10.1016/j.oceaneng.2020.107381 · Cited by 701
A guide to SDG interactions: from science to implementation
Nilsson, M., Griggs, D., McCollum, D., & Stevance, A. (2017) · doi:10.24948/2017.01 · Cited by 568
Dimensions of Blue Carbon and emerging perspectives
Lovelock, C. E., & Duarte, C. M. (2019) · Biology Letters · doi:10.1098/rsbl.2018.0781 · Cited by 529
Blue carbon - A rapid response assessment
Nellemann, C., Corcoran, E. F., Duarte, C. M., Valdés, L., DeYoung, C., Fonseca, L., & Grimsditch, G. (2009) · Environment Science and Policy for Sustainable Development · Cited by 356
Enabling conditions for an equitable and sustainable blue economy
Cisneros-Montemayor, A. M., Moreno‐Báez, M., Reygondeau, G., Cheung, W. W. L., Crosman, K. M., González‐Espinosa, P. C., Lam, V. W. Y., Oyinlola, M. A., Singh, G. G., Swartz, W., et al. (2021) · Nature · doi:10.1038/s41586-021-03327-3 · Cited by 355
OECD (2016) · OECD eBooks · doi:10.1787/9789264251724-en · Cited by 318
OECD Science, Technology and Industry Policy Papers
D., Z., Lenoir, L., Qi, K., Zhe, L., Hrušák, J. (., Caminade, J. P., Chardonnet, C., Barth, M., Müller, V. (., Rizzuto, C., et al. (2013) · OECD science, technology and industry policy papers · doi:10.1787/23074957 · Cited by 310
Development, U. N. C. O. T. A. (2022) · Review of maritime transport · doi:10.18356/9789210021470 · Cited by 262
Financing a sustainable ocean economy
Sumaila, U. R., Walsh, M., Hoareau, K., Cox, A., Teh, L. S. L., Abdallah, P. R., Akpalu, W., Anna, Z., Benzaken, D., Crona, B., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23168-y · Cited by 241
The Essentials of Marine Biotechnology
Rotter, A., Barbier, M., Bertoni, F., Bones, A. M., Cancela, M. L., Carlsson, J., Carvalho, M. F., Cegłowska, M., Martorell, J. C., Dalay, M. C., et al. (2021) · Frontiers in Marine Science · doi:10.3389/fmars.2021.629629 · Cited by 239
Reviving the Ocean Economy: the case for action
Hoegh‐Guldberg, O. (2015) · Cited by 180
Rethinking Innovation for a Sustainable Ocean Economy
OECD (2019) · OECD eBooks · doi:10.1787/9789264311053-en · Cited by 109
2016 Offshore Wind Market Report
Musial, W., Beiter, P., Schwabe, P., Tian, T., Stehly, T. J., & Spitsen, P. (2017) · doi:10.2172/1377012 · Cited by 78
Ocean Solutions That Benefit People, Nature and the Economy
Stuchtey, M., Vincent, A., Merkl, A. A., Bucher, M., Haugan, P. M., Lubchenco, J., & Pangestu, M. E. (2023) · Springer eBooks · doi:10.1007/978-3-031-16277-0_20 · Cited by 77
Electrical drives for direct drive renewable energy systems
Mueller, M. A., & Polinder, H. (2013) · Woodhead Publishing Limited eBooks · doi:10.1533/9780857097491 · Cited by 48
The Ocean as a Solution to Climate Change: Five Opportunities for Action
Hoegh‐Guldberg, O., Caldeira, K., Chopin, T., Gaines, S. D., Haugan, P. M., Hemer, M., Howard, J., Konar, M., Krause‐Jensen, D., Lovelock, C. E., et al. (2023) · Springer eBooks · doi:10.1007/978-3-031-16277-0_17 · Cited by 35
(IPCC), I. P. O. C. C. (2022) · Cambridge University Press eBooks · doi:10.1017/9781009157964.002 · Cited by 32
Technology, Data and New Models for Sustainably Managing Ocean Resources
Leape, J., Abbott, M., Sakaguchi, H., Brett, A., Cao, L., Chand, K., Golbuu, Y., Martin, T., Mayorga, J., & Myksvoll, M. S. (2023) · Springer eBooks · doi:10.1007/978-3-031-16277-0_6 · Cited by 25
Sustainable Blue Economy: Transformation, Value and the Potential of Marine Ecosystems
Knodt, S., Visbeck, M. H., & Biber, A. (2023) · doi:10.1109/oceanslimerick52467.2023.10244621 · Cited by 12
Self-citationHaward, M. (2020) · Routledge eBooks · doi:10.4324/9780367816681-70 · Cited by 7
Flagged first, then by citations
1 of the 23 references couldn’t be matched to a known paper.
Research works printed but not linked: 10
- World Ocean Review (2021): The Ocean, Guarantor of Life - Sustainable Use, Effective Protection. https://worldoceanreview. com/de/wor-7/. Retrieved on 28.04.2022.
- World Ocean Review (2021): The Ocean, Guarantor of Life - Shipping at a turning point. https://worldoceanreview.com/ en/wor-7/transport-over-the-seas/shipping-at-a-turning- point/. Retrieved on 23.05.2022.
- World Ocean Review (2021): The Ocean, Guarantor of Life -The Ocean as energy source -potential and expectations. https://worldoceanreview.com/en/wor-7/energy-and-resources- from-the-ocean/the-ocean-as-energy-source-potential- and-expectations/. Retrieved on 23.05.2022.
- FAO (2020): The State of World Fisheries and Aquaculture 2020. Sustainability in action. Rome. https://doi.org/10.4060/ ca9229en. Retrieved on 23.05.2022. · DOI
- G20 Ministry of the Environment (2021): G20 Report on Actions against Marine Plastic Litter. https://www.env.go.jp/ press/files/jp/117136.pdf. Japan.
- Duarte, C. M, Bruhn, A., & Krause-Jensen, D. (2022): A seaweed aquaculture imperative to meet global sustainability targets. Nat Sustain 5, 185-193. https://doi.org/10.1038/s41893-021- 00773-9. Retrieved on 23.05.2022. · DOI
- Circular Carbon Chemistry (2022): With quantum chemistry and prominent investors to green methanol. Press Release. https://uploads-ssl.webflow.com/62386ab454a40d6f- 52c39913/6244b80c7598dd2117ff8e6c_PM%20C1%20EN.pdf. Retrieved on 23.05.2022.
- Ghasemi, A. (2013): Computational Simulation of the Inter- action Between Moving Rigid Bodies and Two-Fluid Flows. University of Massachusetts Dartmouth, Massachusetts. DOI:10.13140/RG.2.1.4518.9604. Retrieved on 28.04.2022. · DOI
- UN Ocean Conference New York (2017): Factsheet: People and Oceans. https://www.un.org/sustainabledevelopment/ wp-content/uploads/2017/05/Ocean-fact-sheet-package.pdf. Retrieved on 23.05.2022.
- Costello, C. et al. (2020): The future of food from the sea. Nature. https://www.nature.com/articles/s41586-020-2616-y. Retrieved on 25.05.2022.
Cited by
Sorted by citations
Gesami, B. K., & Nunoo, J. (2024) · Frontiers in Marine Science · doi:10.3389/fmars.2024.1404104 · Cited by 41
Sheik, A. G., Kumar, A., Ansari, F. A., Raj, V., Peleato, N. M., Patan, A. K., Kumari, S., & Bux, F. (2024) · Algal Research · doi:10.1016/j.algal.2024.103779 · Cited by 37
Impact of Digital Development and Technology Innovation on the Marine Fishery Economy Quality
Jiang, Y., Huang, L., Liu, Y., & Wang, S. (2024) · Fishes · doi:10.3390/fishes9070266 · Cited by 37
Digital twin development towards integration into blue economy: A bibliometric analysis
Bhati, M., Goerlandt, F., & Pelot, R. P. (2024) · Ocean Engineering · doi:10.1016/j.oceaneng.2024.119781 · Cited by 31
A Digital Twin of the Trondheim Fjord for Environmental Monitoring—A Pilot Case
Vasilijević, A., Brönner, U., Dunn, M., García-Valle, G., Fabrini, J., Stevenson-Jones, R., Bye, B. L., Mayer, I. S., Berre, A. J., Ludvigsen, M., et al. (2024) · Journal of Marine Science and Engineering · doi:10.3390/jmse12091530 · Cited by 29
Self-citationInternational hydrographic survey standards
Mills, G. B. (2023) · The International Hydrographic Review · doi:10.58440/ihr-29-a17 · Cited by 25
Marine digital twins for enhanced ocean understanding
Miedtank, A., Schneider, J., Manss, C., & Zielinski, O. (2024) · Remote Sensing Applications Society and Environment · doi:10.1016/j.rsase.2024.101268 · Cited by 26
Taze, I. E., Hoda, M. A., Miquelez‐Madariaga, I., Maddaloni, P., & Azam, S. E. (2025) · Energies · doi:10.3390/en18133369 · Cited by 16
Roy, M., & Akbar, D. (2025) · Marine Pollution Bulletin · doi:10.1016/j.marpolbul.2025.119028 · Cited by 14
Exploring the Use of Data in a Digital Twin for the Marine and Coastal Environment
Haupt, S., Sibolla, B. H., Molapo, R., Mdakane, L. W., & Fourie, N. (2025) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi14040140 · Cited by 12
Suhardono, S., Fitria, L., Prayogo, W., Lee, C., & Suryawan, I. W. K. (2025) · Journal of Urban Management · doi:10.1016/j.jum.2025.04.008 · Cited by 10
Digital twins of the ocean: Wet environing media and marine futures
Wickberg, A., & Lidström, S. (2025) · New Media & Society · doi:10.1177/14614448251338286 · Cited by 10
A digital-twin strategy using robots for marine ecosystem monitoring
Aguzzi, J., Chatzidouros, E., Chatzievangelou, D., Clavel‐Henry, M., Flögel, S., Bahamón, N., Tangerlini, M., Thomsen, L., Picardi, G., Navarro, J., et al. (2025) · Ecological Informatics · doi:10.1016/j.ecoinf.2025.103409 · Cited by 10
An overview of the ocean data ecosystem
Haimson, M. B., Lehahn, Y., & Sagi, T. (2025) · Ocean science · doi:10.5194/os-21-3131-2025 · Cited by 10
Ye, Y., González-Vidal, A., Cisterna‐García, A., Pérez‐Ruzafa, Á., Izquierdo, M. A. Z., & Skármeta, A. (2025) · Future Generation Computer Systems · doi:10.1016/j.future.2025.108265 · Cited by 10
UAV-Enabled Smart Coastal Environment Monitoring for Marine Litter
Zhang, J., Zhou, X., Huang, Y., Chen, X., & Chen, B. M. (2024) · International Conference on Control and Automation · doi:10.1109/icca62789.2024.10591895 · Cited by 8
Digitalization and Operational Efficiency in Fisheries: Evidence from China
Sun, L., Zhang, L., Jiang, Q., & Zhao, Z. (2024) · Israeli Journal of Aquaculture - Bamidgeh · doi:10.46989/001c.125259 · Cited by 8
Pascàlis, F. D., Urbinati, E., Aalifar, A., Alcázar, L. A., Arpaia, L., Bajo, M., Barbanti, A., Barbariol, F., Bastianini, M., Bellafiore, D., et al. (2025) · Estuarine Coastal and Shelf Science · doi:10.1016/j.ecss.2025.109453 · Cited by 5
Schütte, F., Hans, A. C., Schulz, M., Hummels, R., Assokpa, O., Brandt, P. N., Kiko, R., Körtzinger, A., Fiedler, B., Fischer, T., et al. (2025) · Progress In Oceanography · doi:10.1016/j.pocean.2025.103479 · Cited by 5
Digital Twins of the Ocean: From Idea to Practical Execution – the Paradigm of Iliad
Papachristopoulou, K., Ipektsidis, C., Bye, B. L., Berre, A. J., Sylaios, G. K., van Dam, S., & Chatziapostolidis, M. (2025) · MTS/IEEE OCEANS Conference (OCEANS) · doi:10.1109/oceans58557.2025.11104370 · Cited by 4
Securing Sustainability Through Artificial Intelligence and Blue Economy
Zaeri, N. (2025) · Practice, progress, and proficiency in sustainability · doi:10.4018/979-8-3693-7893-9.ch003 · Cited by 4
Silva, D. V. D., Chen, W., Jacob, B. G., Gramcianinov, C. B., Nam, P. T., Ricker, M., Johnson, K., Pein, J. U., & Staneva, J. V. (2026) · Journal of Environmental Management · doi:10.1016/j.jenvman.2026.128756 · Cited by 3
Error Analysis in Multibeam Hydrographic Survey System
Basil, D. D. (2024) · South African Journal of Geomatics · doi:10.4314/sajg.v13i2.2 · Cited by 3
Sustainability of the Blue Economy in the South Asian Countries
Medhekar, A. (2025) · Practice, progress, and proficiency in sustainability · doi:10.4018/979-8-3693-7893-9.ch004 · Cited by 3
Bai, J., & Ma, Z. (2026) · Marine Policy · doi:10.1016/j.marpol.2026.107042 · Cited by 2
Xue, C., Li, L. C., Liu, J., Su, F., Wu, W., Ma, Z., Xiang, Z., Wu, S., & Qin, Q. (2026) · Digital Twin · doi:10.1080/27525783.2025.2610851 · Cited by 2
Digital twins and cloud computing
Pathare, P. B., Patil, H., Nirmal, N. P., de Waal, J. M., Jagtap, S., Mahanti, N. K., Sharma, P., & Prasath, V. A. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-33750-5.00008-1 · Cited by 2
Establishing a Data Culture Using Frameworks to Navigate the Waves of Marine Data
Flynn, S., Keena, T., Bogan, Y., Brophy, L., Currie, D., Leadbetter, A. M., Maloney, M., Manson, K., Melville, C., O’Grady, E., et al. (2025) · Data Science Journal · doi:10.5334/dsj-2025-024 · Cited by 1
Democratizing marine restoration best practices in a digital toolbox
Veylit, L., Brönner, U., Fischer, K., King, D. M., Stevenson-Jones, S., Dabán, P., Leyva, L., Haro, S., Bouchoucha, M., Monteiro, J. G., et al. (2025) · International Journal of Data Science and Analytics · doi:10.1007/s41060-025-00926-5 · Cited by 1
Self-citationA Model for Co-designing and Co-delivering Ocean Science Knowledge and Solutions
van Noort, C. (2025) · Palgrave studies in maritime politics and security · doi:10.1007/978-3-031-85378-4_2 · Cited by 1
Generative artificial intelligence and marine ecological monitoring
Ortenzi, L., Aguzzi, J., Chatzievangelou, D., Nemmi, E. N., Ferrari, M., Rusiñol, I. M., Clavel‐Henry, M., Bahamón, N., Robinson, N. J., Picardi, G., et al. (2025) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2025.106789 · Cited by 1
Digital Twins of the Ocean: Architecture, Enabling Technologies, and Challenges
Lin, C., Yu, J., He, M., Liu, H., Li, Q., & Liu, J. (2026) · Ocean-Land-Atmosphere Research · doi:10.34133/olar.0160 · Cited by 1
Multimodal Data Fusion in Digital Twin System of Marine RanchingPreprint
Deng, X., Zhu, Y., Chen, M., & Chen, L. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4860801
Basil, D. D. (2024) · Research Square · doi:10.21203/rs.3.rs-4440851/v1
Peters, A. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5250491
The impact of digital economy on the resilience of blue growth in Chinese coastal cities
Wang, Y. (2025) · Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence (DEAI) · doi:10.1145/3745238.3745322
Fonseca, X., Santos, C. P., Hutchinson, K., Hagen, J., de Groot, P., Relouw, J., & Mayer, I. S. (2025) · MTS/IEEE OCEANS Conference (OCEANS) · doi:10.1109/oceans58557.2025.11104517
Papachristopoulou, K., Agorogiannis, E., Ipektsidis, C., Gkioni, A., Parasyris, A., Metheniti, V., & Ristolainen, A. (2025) · International Conference in Electronic Engineering & Information Technology (EEITE) · doi:10.1109/eeite65381.2025.11165883
Inclusion of Artificial Intelligence Towards Achieving Sustainable Development Goals
Zaheer, A., Mishra, K. K., Pant, P., Abdullah, A., & Raghuvanshi, R. (2025) · International Conference on Metaverse and Current Trends in Computing (ICMCTC) · doi:10.1109/icmctc62214.2025.11196408
Zhou, G., Zhang, L., Xu, Y., Hong, L., & Zhang, Y. (2025) · Sustainability · doi:10.3390/su17219464
Integrating Artificial Intelligence in the Blue Economy
Balaji, K. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5238-1.ch007
Sang, Q., Tian, Y., Yu, J., & Zhang, F. (2026) · Ocean Engineering · doi:10.1016/j.oceaneng.2026.124812
Al-Subhiyah, N. H. (2025) · Journal of Strategic and Defense Studies (JSDS) · doi:10.66209/jsds.2025.453
Climate Change, Marine Aquaculture and the Digital Twin
Reid, G. K., Falconer, L., Ytteborg, E., Helmuth, B. S. T., Digre, H., & Kristensen, T. (2026) · Springer eBooks · doi:10.1007/978-3-032-10362-8_7
A Scoping Review of Digital Twins Across Environmental and Territorial Applications
Artioli, L., Borga, G., Costa, P., D’Acunto, F., & Iodice, F. (2026) · Digital · doi:10.3390/digital6030053 · Cited by 1
Immersive Ocean: A Virtual Twin for Participatory Decision Support in Maritime Spatial Planning
Fonseca, X., Santos, C. P., Hutchinson, K., Hagen, J., de Groot, P., Relouw, J., & Mayer, I. S. (2026) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi15070323
Rohma, M. N. (2026) · Journal of Current Studies in SDGs · doi:10.63230/jocsis.3.3.204
Nurcholidah, L., Haryono, T., Sunaryo, S., & Hendarsjah, H. (2026) · Journal of Current Studies in SDGs · doi:10.63230/jocsis.3.3.203
Energy Shocks, Sovereign Capital Structure, and the Blue Economy
Rehan, R., Jamal, Y., Premananto, G. C., & Zakaria, M. H. B. (2026) · IGI Global eBooks · doi:10.4018/979-8-2600-1298-7.ch001
Fonseca, X., & Mayer, I. S. (2026) · Ocean & Coastal Management · doi:10.1016/j.ocecoaman.2026.108398
DIVE: Digital Twin for Innovation in Oceanic Visualization and Exploration
Datcu, M. P., Danisor, C., Jancauskas, V., Espinoza-Molina, D., Garske, S., Fellegara, R., Zeumer, M., Ratha, D., Camus, L., Hirvoas, A., et al. (2026) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss60577.2026.11731024
Metadata
- Authors
- Brönner, U., Sonnewald, M., & Visbeck, M.
- Affiliations
- Christian-Albrechts-Universität zu Kiel (DE)
- Venue
- The International Hydrographic Review
- Published
- 2023-05-01
- Volume
- 29
- Issue
- 1
- Pages
- 26-40
- ISSN
- 0020-6946 (ISSN-L)
- OpenAlex
- W4367611274
- Cited by
- 49
- References
- 23
- Citations by year
- 2026: 13 · 2025: 24 · 2024: 11 · 2023: 1
- FWCI
- 13.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The International Hydrographic Review (publishedVersion)
- Helmholtz Centre for Ocean Research Kiel (GEOMAR) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Environmental Science › Management, Monitoring, Policy and Law › Coastal and Marine Management
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Environmental Science › Management, Monitoring, Policy and Law › Environmental Monitoring and Data Management
- Keywords
- blue economy, marine protected areas, ocean governance, ocean modeling, oceanographic observations, Internet of Things, artificial intelligence, machine learning, data spaces, climate change, marine pollution, overfishing, sustainable ocean development, decision support
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
