Digital Twins for Research and Innovation in Support of the European Green Deal Data Space: A Systematic Review
Abstract
:1. Introduction
2. Background
2.1. Data Spaces
2.1.1. European Open Science Cloud
- Stage 1 (2021–2022): to deploy the core technical functions (EOSC Core) that enable the operations of the EOSC.
- Stage 2 (2023–2024): to expand the core data infrastructure for scientific research in key thematic areas as well as to connect the EOSC to the wider public sector (e.g., INSPIRE) and the private sector (e.g., Gaia-X).
- Stage 3 (2025–2027 and beyond): to enable European and national research infrastructures delivered from the Member States and Associated Countries to further expand the EOSC.
2.1.2. Green Deal Data Space
- Community of Practice (CoP): Open CoP of data providers, users, and intermediaries from diverse stakeholder communities participating in all phases from co-design to implementation, supported by use cases identified by the DSSC [44].
- Blueprint: The reference of the technical architecture setting the data and service technical interoperability framework and defining the common services enabling federated discovery, access, processing, and reuse of data [44].
- Priority dataset: The Minimum Viable GDDS, defining an expandable core set of high-value datasets for the first implementation phase of the data ecosystem federation [45].
- Governance and Business Models: An open and inclusive multi-stakeholder governance scheme defining federation business processes, roles, and policies and the trust framework [46].
- Roadmap: The high-level roadmap defining the future implementation (2025–2027) and capacity building steps [47].
2.1.3. Technical Building Blocks for Data Spaces
- T1. Data interoperability enables the exchange of data, such as semantic data models, data formats, and interface APIs, including functionalities for provenance and tracking the processing of data sharing.
- T2. Data sovereignty and trust enable the identification of participants and assets in a data space, sovereignty over their shared data and the enforcement of policies agreed on regarding data access and usage control.
- T3. Data value creation enables data providers to register data offerings or services, publish their description to be discovered following the FAIR principles, and provide marketplace functionality.
2.2. Digital Twins
2.2.1. Digital Twin of the Earth
2.2.2. Digital Twin of the Ocean
2.3. Research and Innovation (R&I) Relationship between EOSC, Data Spaces, and DTs
3. Materials and Methods
3.1. Data Collection
- Web of Science: all databases.
- CORDIS: 10,045 HORIZON projects.
3.2. Search Strategy
- (data space*), selected 6287 articles;
- (digital twin*), selected 11,842 articles;
- (EOSC OR (European Open Science Cloud)), selected 133 articles;
- (data space* AND digital twin*), selected 18 articles that mention both keywords to reflect our main interest.
- (data space*) AND (EOSC OR (European Open Science Cloud)), selected 1 article;
- (digital twin*) AND (EOSC OR (European Open Science Cloud)), selected 1 article;
- (data space*) AND (digital twin*) AND (EOSC OR (European Open Science Cloud) selected 0 articles.
- (data space*), selected 81 projects;
- (digital twin*), selected 163 projects;
- (EOSC OR (European Open Science Cloud)), selected 49 projects;
- (data space*) AND (digital twin*), selected 18 projects;
- (data space*) AND (EOSC OR (European Open Science Cloud)), selected 12 projects;
- (digital twin*) AND (EOSC OR (European Open Science Cloud)), selected 4 projects;
- (data space*) AND (digital twin*) AND (EOSC OR (European Open Science Cloud), selected 2 projects.
3.3. Data Extraction and Criteria
- Data spaces contributing to the Green Deal (environmental data);
- DTs of the Earth (Earth observations);
- EOSC-related projects contributing to the Green Deal.
3.4. Technical Building Block Evaluation
4. Results
4.1. Web of Science Articles
4.2. CORDIS—HORIZON Projects
4.2.1. Connection between Data Spaces and DTs
4.2.2. Connection between Data Spaces and EOSC
4.2.3. Connection between DTs and EOSC
4.3. Technical Building Blocks for GDDS
5. Discussion
6. Conclusions
- A top-down approach with fundamental infrastructures composed of well-defined technical building blocks as the reference framework, such as the EOSC EU node, as well as technical guidelines (e.g., the DSSC) and accepted standard implementation (e.g., SIMPL and other intermediary services) to accelerate digital transformation within and across sectors to enhance the integration between platforms across domains.
- A bottom-up approach with flexibility and robustness of service components contributed by various technologies adopted by different initiatives to increase the interoperability as well as support the implementation of the GDDS with EU research projects in collaboration with the DT initiatives (e.g., DestinE).
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Qi, Q.; Tao, F. Digital Twin and Big Data towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison. IEEE Access 2018, 6, 3585–3593. [Google Scholar] [CrossRef]
- Tao, F.; Qi, Q. Make more digital twins. Nature 2019, 573, 490–491. [Google Scholar] [CrossRef] [PubMed]
- European Commission, Joint Research Centre. Towards a Green & Digital Future: Key Requirements for Successful Twin Transitions in the European Union. 2022. Available online: https://data.europa.eu/doi/10.2760/977331 (accessed on 11 March 2024).
- European Commission. Implementation Roadmap for the European Open Science Cloud; EC Staff Working Document, COM(2018) 83 Final; European Commission: Brussels, Belgium, 2018. [Google Scholar]
- Abbott, A.; Butler, D.; Gibney, E.; Schiermeier, Q.; Van Noorden, R. Boon or burden: What has the EU ever done for science? Nature 2016, 534, 307–309. [Google Scholar] [CrossRef] [PubMed]
- European Commission. Realising the European Open Science Cloud. First Report and Recommendations of the Commission High Level Expert Group on the European Open Science Cloud; European Commission: Brussels, Belgium, 2016. [Google Scholar]
- European Commission. A European Strategy for Data; EC Staff Working Document, COM(2020) 66 Final; European Commission: Brussels, Belgium, 2020. [Google Scholar]
- European Commission. Data Spaces; EC Staff Working Document; European Commission: Brussels, Belgium, 2024. [Google Scholar]
- European Commission. Annex 1—Implementing Decision amending Implementing Decision C (2023) 1862 Final on the Financing of the Digital Europe Programme and the Adoption of the Work Programme for 2023–2024. 2023. Available online: https://digital-strategy.ec.europa.eu/en/library/annex-amendment-digital-europe-programme-work-programmes-2023-2024 (accessed on 9 May 2024).
- European Commission. Common European Data Spaces; EC Staff Working Document; European Commission: Brussels, Belgium, 2022. [Google Scholar]
- European Commission. Shaping Europe’s Digital Future; European Commission: Brussels, Belgium, 2022. [Google Scholar]
- Bauer, P.; Stevens, B.; Hazeleger, W. A digital twin of Earth for the green transition. Nat. Clim. Chang. 2021, 11, 2. [Google Scholar] [CrossRef]
- Neethirajan, S.; Kemp, B. Digital Twins in Livestock Farming. Animals 2021, 11, 1008. [Google Scholar] [CrossRef]
- Ariesen-Verschuur, N.; Verdouw, C.; Tekinerdogan, B. Digital Twins in greenhouse horticulture: A review. Comput. Electron. Agric. 2022, 199, 107183. [Google Scholar] [CrossRef]
- Nasirahmadi, A.; Hensel, O. Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm. Sensors 2022, 22, 498. [Google Scholar] [CrossRef]
- Melesse, T.Y.; Franciosi, C.; Di Pasquale, V.; Riemma, S. Analyzing the Implementation of Digital Twins in the Agri-Food Supply Chain. Logistics 2023, 7, 33. [Google Scholar] [CrossRef]
- Purcell, W.; Neubauer, T. Digital Twins in Agriculture: A State-of-the-art review. Smart Agric. Technol. 2023, 3, 100094. [Google Scholar] [CrossRef]
- Peladarinos, N.; Piromalis, D.; Cheimaras, V.; Tserepas, E.; Munteanu, R.A.; Papageorgas, P. Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review. Sensors 2023, 23, 7128. [Google Scholar] [CrossRef]
- Silva, L.; Rodríguez-Sedano, F.; Baptista, P.; Coelho, J.P. The Digital Twin Paradigm Applied to Soil Quality Assessment: A Systematic Literature Review. Sensors 2023, 23, 1007. [Google Scholar] [CrossRef] [PubMed]
- Wang, L. Digital Twins in Agriculture: A Review of Recent Progress and Open Issues. Electronics 2024, 13, 2209. [Google Scholar] [CrossRef]
- Tagarakis, A.C.; Benos, L.; Kyriakarakos, G.; Pearson, S.; Sørensen, C.G.; Bochtis, D. Digital Twins in Agriculture and Forestry: A Review. Sensors 2024, 24, 3117. [Google Scholar] [CrossRef] [PubMed]
- Escribà-Gelonch, M.; Liang, S.; van Schalkwyk, P.; Fisk, I.; Van Duc Long, N.; Hessel, V. Digital Twins in Agriculture: Orchestration and Applications. Agric. Food Chem. 2024, 72, 10737–10752. [Google Scholar] [CrossRef] [PubMed]
- Føre, M.; Alver, M.O.; Alfredsen, J.A.; Rasheed, A.; Hukkelås, T.; Bjelland, H.V.; Su, B.; Ohrem, S.J.; Kelasidi, E.; Norton, T.; et al. Digital Twins in intensive aquaculture—Challenges, opportunities and future prospects. Comput. Electron. Agric. 2024, 218, 108676. [Google Scholar] [CrossRef]
- Symeonaki, E.; Maraveas, C.; Arvanitis, K.G. Recent Advances in Digital Twins for Agriculture 5.0: Applications and Open Issues in Livestock Production Systems. Appl. Sci. 2024, 14, 686. [Google Scholar] [CrossRef]
- Guo, H.; Nativi, S.; Liang, D.; Craglia, M.; Wang, L.; Schade, S.; Annoni, A. Big Earth Data science: An information framework for a sustainable planet. Int. J. Digit. Earth 2020, 13, 743–767. [Google Scholar] [CrossRef]
- Yu, D.; He, Z. Digital twin-driven intelligence disaster prevention and mitigation for infrastructure: Advances, challenges, and opportunities. Nat. Hazards 2022, 112, 1–36. [Google Scholar] [CrossRef]
- DeFelipe, I.; Alcalde, J.; Baykiev, E.; Bernal, I.; Boonma, K.; Carbonell, R.; Flude, S.; Folch, A.; Fullea, J.; García-Castellanos, D.; et al. Towards a Digital Twin of the Earth System: Geo-Soft-CoRe, a Geoscientific Software & Code Repository. Front. Earth Sci. 2022, 10, 828005. [Google Scholar] [CrossRef]
- Li, X.; Feng, M.; Ran, Y. Big Data in Earth system science and progress towards a digital twin. Nat. Rev. Earth Environ. 2023, 4, 319–332. [Google Scholar] [CrossRef]
- Riaz, K.; McAfee, M.; Gharbia, S.S. Management of Climate Resilience: Exploring the Potential of Digital Twin Technology, 3D City Modelling, and Early Warning Systems. Sensors 2023, 23, 2659. [Google Scholar] [CrossRef] [PubMed]
- Barricelli, B.R.; Casiraghi, E.; Fogli, D. A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications. IEEE Access 2019, 7, 167653–167671. [Google Scholar] [CrossRef]
- Nativi, S.; Mazzetti, P.; Craglia, M. Digital Ecosystems for Developing Digital Twins of the Earth: The Destination Earth Case. Remote Sens. 2021, 13, 2119. [Google Scholar] [CrossRef]
- Otto, B.; ten Hompel, M.; Wrobel, S. Designing Data Spaces: The Ecosystem Approach to Competitive Advantage; Springer International Publishing: Cham, Switzerland, 2021. [Google Scholar] [CrossRef]
- Curry, E.; Scerri, S.; Tuikka, T. Data Spaces: Design, Deployment, and Future Directions; Springer International Publishing: Cham, Switzerland, 2022. [Google Scholar] [CrossRef]
- European Commission. EOSC: The Transverse European Data Space for Science, Research and Innovation; Statement; European Commission: Brussels, Belgium, 2022. [Google Scholar] [CrossRef]
- Kotsev, A.; Minghini, M.; Tomas, R.; Cetl, V.; Lutz, M. From Spatial Data Infrastructures to Data Spaces—A Technological Perspective on the Evolution of European SDIs. ISPRS Int. J. Geo-Inf. 2020, 9, 176. [Google Scholar] [CrossRef]
- ENVRI. ENVRI-FAIR. 2024. Available online: https://envri.eu/the-envri-fair-project (accessed on 29 April 2024).
- Wilkinson, M.D. Comment: The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 2016, 3, 160018. [Google Scholar] [CrossRef]
- Budroni, P.; De Loof, C.; de Mello Castro Giroletti, J.; Robertson, D.; Schröder-Panderand, F.; Caetano, I. EOSC Focus—D3.1—EOSC Technical Collaboration with other European Partnerships and Relevant Initiatives; EOSC Focus: Brussels, Belgium, 2024. [Google Scholar] [CrossRef]
- European Commission. The European Green Deal Striving to be the First Climate-Neutral Continent. 2024. Available online: https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal_en (accessed on 29 April 2024).
- European Commission, Joint Research Centre (JRC). Beyond INSPIRE. Perspectives on the Legal Foundation of the European Green Deal Data Space; European Commission: Brussels, Belgium, 2023. [Google Scholar]
- Kotsev, A.; Minghini, M.; Cetl, V.; Penninga, F.; Robbrecht, J.; Lutz, M. INSPIRE A Public Sector Contribution to the European Green Deal Data Space A vision for the Technological Evolution of Europe’s Spatial Data Infrastructures for 2030; European Commission: Brussels, Belgium, 2021. [Google Scholar] [CrossRef]
- Lush, V.; Bastin, L.; Otsu, K.; Masó, J. Assessing FAIRness of citizen science data in the context of the Green Deal Data Space. Int. J. Digit. Earth 2024, 17, 1. [Google Scholar] [CrossRef]
- GREAT. Green Deal Data Space Foundation and its Community of Practice. 2024. Available online: https://www.greatproject.eu (accessed on 29 April 2024).
- GREAT. Green Deal Data Space Foundation and Its Community of Practice D3.2: Final Blueprint of the GDDS Reference Architecture. 2024. Available online: https://www.greatproject.eu/wp-content/uploads/2024/04/D3.2-Final-Blueprint-of-the-GDDS-Reference-Architecture.pdf (accessed on 29 April 2024).
- GREAT. Green Deal Data Space Foundation and Its Community of Practice D5.2: EGD Prioritised Datasets and Gaps (Initial Inventory Plus All Reference Use Cases). 2024. Available online: https://www.greatproject.eu/wp-content/uploads/2024/04/D5.2-EGD-Prioritised-Datasets-and-Gaps-Initial-Inventory-plus-all-Reference-Use-Cases.pdf (accessed on 29 April 2024).
- GREAT. Green Deal Data Space and Foundation and its Community of Practice (GREAT) D4.2 Final Governance Requirements and Endorsed Governance Scheme. 2024. Available online: https://www.greatproject.eu/wp-content/uploads/2024/04/D4.2-Final-Governance-Requirements-and-Endorsed-Governance-Scheme.pdf (accessed on 29 April 2024).
- GREAT. Green Deal Data Space Foundation and its Community of Practice D6.1: Green Deal Data Space Implementation Roadmap. 2022. Available online: https://www.greatproject.eu/wp-content/uploads/2023/11/D6.1-Roadmap.v1.0-2.pdf (accessed on 29 April 2024).
- Data Spaces Support Centre (DSSC). Data Spaces Blueprint v1.0. 2024. Available online: https://dssc.eu/space/BVE/357074917/Technical+Building+Blocks (accessed on 30 April 2024).
- International Organization for Standardization (ISO). ISO 23247-1; Automation Systems and Integration Digital Twin Framework for Manufacturing. ISO: Geneva, Switzerland, 2021. Available online: https://www.iso.org/standard/75066.html (accessed on 29 April 2024).
- Volz, F.; Sutschet, G.; Stojanovic, L.; Usländer, T. On the Role of Digital Twins in Data Spaces. Sensors 2023, 23, 7601. [Google Scholar] [CrossRef] [PubMed]
- Gao, C.; Wang, J.; Dong, S.; Liu, Z.; Cui, Z.; Ma, N.; Zhao, X. Application of Digital Twins and Building Information Modeling in the Digitization of Transportation: A Bibliometric Review. Appl. Sci. 2022, 12, 11203. [Google Scholar] [CrossRef]
- Visartsakul, B.; Damrianant, J. A Review of Building Information Modeling and Simulation as Virtual Representations Under the Digital Twin Concept. Eng. J. 2022, 27, 11–27. [Google Scholar] [CrossRef]
- Drobnyi, V.; Hu, Z.; Fathy, Y.; Brilakis, I. Construction and Maintenance of Building Geometric Digital Twins: State of the Art Review. Sensors 2023, 23, 4382. [Google Scholar] [CrossRef]
- Hu, W.; Lim, K.Y.H.; Cai, Y. Digital Twin and Industry 4.0 Enablers in Building and Construction: A Survey. Buildings 2022, 12, 2004. [Google Scholar] [CrossRef]
- Tuhaise, V.V.; Tah, J.H.M.; Abanda, F.H. Technologies for digital twin applications in construction. Autom. Constr. 2023, 152, 104931. [Google Scholar] [CrossRef]
- Zhang, Z.; Wei, Z.; Court, S.; Yang, L.; Wang, S.; Thirunavukarasu, A.; Zhao, Y. A Review of Digital Twin Technologies for Enhanced Sustainability in the Construction Industry. Buildings 2024, 14, 1113. [Google Scholar] [CrossRef]
- Kosacka-Olejnik, M.; Kostrzewski, M.; Marczewska, M.; Mrówczyńska, B.; Pawlewski, P. How Digital Twin Concept Supports Internal Transport Systems?—Literature Review. Energies 2021, 14, 4919. [Google Scholar] [CrossRef]
- Kajba, M.; Jereb, B.; Cvahte Ojsteršek, T. Exploring Digital Twins in the Transport and Energy Fields: A Bibliometrics and Literature Review Approach. Energies 2023, 16, 3922. [Google Scholar] [CrossRef]
- Liebenberg, M.; Jarke, M. Information systems engineering with Digital Shadows: Concept and use cases in the Internet of Production. Inf. Syst. 2023, 114, 102182. [Google Scholar] [CrossRef]
- Rucco, C.; Longo, A.; Zappatore, M. Supporting Energy Digital Twins with Cloud Data Spaces: An Architectural Proposal. In Lecture Notes in Computer Science; Springer Science and Business Media: Berlin/Heidelberg, Germany, 2022; pp. 47–58. [Google Scholar] [CrossRef]
- El Saddik, A. Digital Twins: The Convergence of Multimedia Technologies. IEEE MultiMedia 2018, 25, 87–92. [Google Scholar] [CrossRef]
- Rathore, M.M.; Shah, S.A.; Shukla, D.; Bentafat, E.; Bakiras, S. The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities. IEEE Access 2021, 9, 32030–32052. [Google Scholar] [CrossRef]
- Nativi, S.; Delipetrev, B.; Craglia, M. Destination Earth Survey on ‘Digital Twins’ Technologies and Activities, in the Green Deal Area; European Commission: Brussels, Belgium, 2021. [Google Scholar] [CrossRef]
- Destination Earth. Destination Earth Data Lake 0.0.1 Documentation. Available online: https://destine-data-lake-docs.data.destination-earth.eu/en/latest/index.html (accessed on 30 April 2024).
- Schick, S. Destination Earth Data Lake by EUMETSAT. In 1st Destination Earth User eXchange; European Commission: Brussels, Belgium, 2023; Available online: https://destination-earth.eu/wp-content/uploads/2023/05/10.-Michael-Schick.pdf (accessed on 6 May 2024).
- European Commission. European Missions Restore Our Ocean and Waters by 2030 Implementation Plan; European Commission: Brussels, Belgium, 2021. [Google Scholar]
- Tzachor, A.; Hendel, O.; Richards, C.E. Digital twins: A stepping stone to achieve ocean sustainability? NPJ Ocean Sustain. 2023, 2, 16. [Google Scholar] [CrossRef]
- European Commission. European Digital Twin of the Ocean (European DTO). Available online: https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/funding-programmes-and-open-calls/horizon-europe/eu-missions-horizon-europe/restore-our-ocean-and-waters/european-digital-twin-ocean-european-dto_en (accessed on 29 April 2024).
- Vrana, J. NDE Perception and Emerging Reality: NDE 4.0 Value Extraction. Mater. Eval. 2020, 78, 835–851. [Google Scholar] [CrossRef]
- Jacoby, M.; Volz, F.; Weißenbacher, C.; Stojanovic, L.; Usländer, T. An approach for Industrie 4.0-compliant and data-sovereign Digital Twins Realization of the Industrie 4.0 Asset Administration Shell with a data-sovereignty extension. at-Automatisierungstechnik 2021, 69, 1051–1061. [Google Scholar] [CrossRef]
- Harjula, I. Smart Manufacturing Multi-Site Testbed with 5G and beyond Connectivity. In Proceedings of the IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Helsinki, Finland, 13–16 September 2021. [Google Scholar] [CrossRef]
- Li, H. Data-driven hybrid petri-net based energy consumption behaviour modelling for digital twin of energy-efficient manufacturing system. Energy 2022, 239, 122178. [Google Scholar] [CrossRef]
- Yang, W.; Zheng, Y.; Li, S. Digital twin of spacecraft assembly cell and case study. Int. J. Comput. Integr. Manuf. 2022, 35, 3. [Google Scholar] [CrossRef]
- Moreno, T.; Almeida, A.; Toscano, C.; Ferreira, F.; Azevedo, A. Scalable Digital Twins for industry 4.0 digital services: A dataspaces approach. Prod. Manuf. Res. 2023, 11, 1. [Google Scholar] [CrossRef]
- van Dyck, M.; Lüttgens, D.; Piller, F.T.; Brenk, S. Interconnected digital twins and the future of digital manufacturing: Insights from a Delphi study. J. Prod. Innov. Manag. 2023, 40, 475–505. [Google Scholar] [CrossRef]
- Tolio, T.A.M.; Monostori, L.; Váncza, J.; Sauer, O. Platform-based manufacturing. CIRP Ann. 2023, 72, 697–723. [Google Scholar] [CrossRef]
- Zhang, C. A multi-level modelling and fidelity evaluation method of digital twins for creating smart production equipment in Industry 4.0. Int. J. Prod. Res. 2024, 62, 10. [Google Scholar] [CrossRef]
- Niccolucci, F.; Felicetti, A.; Hermon, S. Populating the Data Space for Cultural Heritage with Heritage Digital Twins. Data 2022, 7, 105. [Google Scholar] [CrossRef]
- Solmaz, G. Enabling data spaces: Existing developments and challenges. In DE 2022—Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022, Rome, Italy, 9 December 2022; Association for Computing Machinery, Inc.: New York, NY, USA, 2022; pp. 42–48. [Google Scholar] [CrossRef]
- Jobst, M.; Gartner, G. Accessing spatial knowledge networks with maps. Int. J. Cartogr. 2022, 8, 1. [Google Scholar] [CrossRef]
- Elia, D.; Antonio, F.; Fiore, S.; Nassisi, P.; Aloisio, G. A Data Space for Climate Science in the European Open Science Cloud. Comput. Sci. Eng. 2023, 25, 7–15. [Google Scholar] [CrossRef]
- Dañobeitia, J.J. The role of the marine research infrastructures in the European marine observation landscape: Present and future perspectives. Front. Mar. Sci. 2023, 10, 2023. [Google Scholar] [CrossRef]
- Beverungen, D.; Hess, T.; Köster, A.; Lehrer, C. From private digital platforms to public data spaces: Implications for the digital transformation. Electron. Mark. 2022, 32, 493–501. [Google Scholar] [CrossRef]
- EOSC Association Board of Directors. EOSC Association Board Position Paper on the EOSC Federation and the Role of EOSC Nodes. 2023. Available online: https://eosc.eu/wp-content/uploads/2024/03/EOSC-A-Board-Position-Paper-on-the-EOSC-Federation-version-20231112.pdf (accessed on 30 April 2024).
- Copernicus. Copernicus Data Space Ecosystem Documentation. 2024. Available online: https://documentation.dataspace.copernicus.eu/Home.html (accessed on 9 May 2024).
- Escriu, J.; Minghini, M.; Kotsev, A. Towards spatial and open data discoverability for European Data Spaces. In Joint EuroGeographics and EuroSDR Virtual Workshop on Geodata Discovery; European Commission: Brussels, Belgium, 2024; Available online: https://eurogeographics.org/app/uploads/2023/06/04.-20240116_Towards_spatial_and_open_data_discoverability_for_EU_Data_Spaces-JRC_ESCRIU.pdf (accessed on 15 May 2024).
- Boldrini, E.; Nativi, S.; Hradec, J.; Santoro, M.; Mazzetti, P.; Craglia, M. GEOSS Platform data content and use. Int. J. Digit. Earth 2023, 16, 1. [Google Scholar] [CrossRef]
- International Organization for Standardization (ISO). ISO 19115-2; Geographic Information—Metadata Part 2: Extensions for Acquisition and Processing. ISO: Geneva, Switzerland, 2019. Available online: https://www.iso.org/standard/67039.html (accessed on 25 September 2024).
- International Organization for Standardization (ISO). ISO 16363; Space Data and Information Transfer Systems—Audit and Certification of Trustworthy Digital Repositories. ISO: Geneva, Switzerland, 2012. Available online: https://www.iso.org/standard/56510.html (accessed on 25 September 2024).
- International Organization for Standardization (ISO). ISO 19115-1; Geographic Information—Metadata Part 1: Fundamentals. ISO: Geneva, Switzerland, 2014. Available online: https://www.iso.org/standard/53798.html (accessed on 25 September 2024).
- International Organization for Standardization (ISO). ISO/TS 19139-1; Geographic Information—XML Schema Implementation Part 1: Encoding Rules. ISO: Geneva, Switzerland, 2019. Available online: https://www.iso.org/standard/67253.html (accessed on 25 September 2024).
- AD4GD All Data 4 Green Deal. Available online: https://ad4gd.eu/deliverables (accessed on 22 April 2024).
- AquaINFRA Infrastructure for Marine and Inland Water Research. Available online: https://cordis.europa.eu/project/id/101094434/results (accessed on 22 April 2024).
- International Organization for Standardization (ISO). ISO/TC 211; Geographic Information/Geomatics. ISO: Geneva, Switzerland, 1994. Available online: https://www.iso.org/committee/54904.html (accessed on 25 September 2024).
- ASPECT Adaptation-Oriented Seamless Predictions of European ClimaTe. Available online: https://www.aspect-project.eu/public-deliverables (accessed on 26 April 2024).
- B3 Biodiversity Building Blocks for Policy. Available online: https://b-cubed.eu/library (accessed on 22 April 2024).
- Blue-Cloud 2026 A federated European FAIR and Open Research Ecosystem for Oceans, Seas, Coastal and INLAND waters. Available online: https://cordis.europa.eu/project/id/101094227/results (accessed on 22 April 2024).
- DT-GEO A Digital Twin for GEOphysical Extremes. Available online: https://cordis.europa.eu/project/id/101058129/results (accessed on 22 April 2024).
- EDITO-Infra EU Public Infrastructure for the European DIgital Twin Ocean. Available online: https://cordis.europa.eu/project/id/101101473/results (accessed on 1 July 2024).
- EDITO-Model Lab Underlying models for the European DIgital Twin Ocean. Available online: https://edito-modellab.eu/results (accessed on 1 July 2024).
- ENVRI-Hub NEXT ENVironmental Research Infrastructures Delivering an Open Access Hub and NEXT-Level Interdisciplinary Research Framework Providing Services for Advancing Science and Society. Available online: https://envri.eu/envri-hub-next (accessed on 26 April 2024).
- FAIR-EASE FAIR EArth Sciences & Environment Services. Available online: https://cordis.europa.eu/project/id/101058785/results (accessed on 22 April 2024).
- FAIRiCUBE F.A.I.R. Information Cube. Available online: https://fairicube.nilu.no/deliverables2 (accessed on 22 April 2024).
- Green.Dat.AI Energy-Efficient AI-Ready Data Spaces. Available online: https://greendatai.eu/deliverables (accessed on 22 April 2024).
- Iliad Integrated DigitaL Framework For Comprehensive Maritime Data and Information Services. Available online: https://cordis.europa.eu/project/id/101037643/results (accessed on 22 April 2024).
- iMagine Imaging Data and Services for Aquatic Science. Available online: https://cordis.europa.eu/project/id/101058625/results (accessed on 26 April 2024).
- IMMERSE Improving Models for Marine EnviRonment Services. Available online: https://cordis.europa.eu/project/id/821926/results (accessed on 22 April 2024).
- CEA. CNRS INRIA Logiciel Libre (CeCILL). CECILL-2. 2006. Available online: https://cecill.info/licences/Licence_CeCILL_V2-en.txt (accessed on 25 September 2024).
- interTwin. An Interdisciplinary Digital Twin Engine for Science. Available online: https://cordis.europa.eu/project/id/101058386/results (accessed on 26 April 2024).
- IRISCC Integrated Research Infrastructure Services for Climate Change Risks. Available online: https://www.iriscc.eu/resources (accessed on 26 April 2024).
- LandSeaLot Land-Sea Interface: Let’s Observe Together! Available online: https://landsealot.eu/resources (accessed on 26 April 2024).
- USAGE Urban Data Spaces for Green dEal. Available online: https://www.usage-project.eu/deliverables (accessed on 22 April 2024).
- International Organization for Standardization (ISO). ISO 19131; Geographic Information—Data Product Specifications. ISO: Geneva, Switzerland, 2022. Available online: https://www.iso.org/standard/85092.html (accessed on 25 September 2024).
- Waterverse Water Data Management Ecosystem for Water Data Spaces. Available online: https://cordis.europa.eu/project/id/101070262/results (accessed on 26 April 2024).
- Otto, B. A federated infrastructure for European data spaces. Commun. ACM 2022, 65, 44–45. [Google Scholar] [CrossRef]
- EGI Foundations. EGI Contribution to the EOSC Federation Discussion Paper; EGI Foundations: Amsterdam, The Netherlands, 2024. [Google Scholar] [CrossRef]
- European Commission. Preparatory Work in View of the Procurement of an Open Source Cloud-to-Edge Middleware Platform. 2022. Available online: https://digital-strategy.ec.europa.eu/en/policies/simpl#1712822729753-0 (accessed on 11 March 2024).
- European Commission. European Open Science Cloud: EU Node. 2024. Available online: https://open-science-cloud.ec.europa.eu/about/eosc-eu-node (accessed on 29 April 2024).
- European Commission. Launching and Operating the EOSC EU Node. 2024. Available online: https://eosc.eu/wp-content/uploads/2024/02/Peter-Szegedi-European-Commission-Winter-school-2024.pdf (accessed on 30 April 2024).
- EOSC Beyond. Pilots. Available online: https://www.eosc-beyond.eu/pilots (accessed on 15 May 2024).
- European Commission. Horizon Europe Work Programme 2021–2022 Research Infrastructures; European Commission: Brussels, Belgium, 2021. [Google Scholar]
- European Commission. H2020 Work Programme 2018–2020 General Introduction; European Commission: Brussels, Belgium, 2020. [Google Scholar]
- Siska, V.; Karagiannis, V.; Drobics, M. Building a Dataspace: Technical Overview. Gaia-X Hub Austria 2023. Available online: https://www.gaia-x.at/wp-content/uploads/2023/04/WhitepaperGaiaX.pdf (accessed on 11 March 2024).
- Rajani, R. Trust Framework in Dataspaces by iSHARE Foundation. 2024. Available online: https://www.data-spaces-symposium.eu/wp-content/uploads/2024/03/08.-TrustFramework-DSS-2024-Rajiv-Rajani.pdf (accessed on 30 April 2024).
- Zhao, Z.; Hellström, M. Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges; Springer Nature: Cham, Switzerland, 2020. [Google Scholar] [CrossRef]
- International Data Spaces Association. IDSA Data Connector Report 14. 2024. Available online: https://internationaldataspaces.org/wp-content/uploads/dlm_uploads/IDSA-Data-Connector-Report-14_April-2024-3.pdf (accessed on 30 April 2024).
- Kouloglou, I.-O.; Antzoulatos, G.; Vosinakis, G.; Lombardo, F.; Abella, A.; Bakratsas, M.; Moumtzidou, A.; Maltezos, E.; Gialampoukidis, I.; Ouzounoglou, E. FIWARE-Compatible Smart Data Models for Satellite Imagery and Flood Risk Assessment to Enhance Data Management. Information 2024, 15, 257. [Google Scholar] [CrossRef]
- Eclipse Dataspace Components. Available online: https://github.com/eclipse-edc (accessed on 1 July 2024).
T1. Data Interoperability | T2. Data Sovereignty | T3. Data Value Creation |
---|---|---|
Data Model | Access and Usage | Metadata |
Data Exchange | Identity | Publish and Discover |
Provenance and Traceability | Trust Framework | Value-Added |
Keyword | data space* | digital twin* | EOSC |
---|---|---|---|
data space* | 6287 | 18 | 1 |
digital twin* | 18 | 11,842 | 1 |
EOSC | 1 | 1 | 133 |
Keyword | data space* | digital twin* | EOSC |
---|---|---|---|
data space* | 81 | 18 | 12 |
digital twin* | 18 | 163 | 4 |
EOSC | 12 | 4 | 49 |
Sector | Publication Year | Title | Authors |
---|---|---|---|
Industry | 2020 | NDE Perception and Emerging Reality: NDE 4.0 Value Extraction | Vrana, J. [69] |
2021 | An approach for Industrie 4.0-compliant and data-sovereign Digital Twins | Jacoby, M. et al. [70] | |
2021 | Smart Manufacturing Multi-Site Testbed with 5G and Beyond Connectivity | Harjula, I. et al. [71] | |
2022 | Data-driven hybrid petri-net based energy consumption behaviour modelling for digital twin of energy-efficient manufacturing system | Li, H.C. et al. [72] | |
2022 | Digital twin of spacecraft assembly cell and case study | Yang, W.Q. et al. [73] | |
2023 | On the Role of Digital Twins in Data Spaces | Volz, F. et al. [50] | |
2023 | Scalable Digital Twins for industry 4.0 digital services: a dataspaces approach | Moreno, T. et al. [74] | |
2023 | Interconnected digital twins and the future of digital manufacturing: Insights from a Delphi study | van Dyck, M. et al. [75] | |
2023 | Platform-based manufacturing | Tolio, TAM et al. [76] | |
2023 | A multi-level modelling and fidelity evaluation method of digital twins for creating smart production equipment in Industry 4.0 | Zhang, C. et al. [77] | |
2023 | Information systems engineering with Digital Shadows: Concept and use cases in the Internet of Production | Liebenberg, M. and Jarke, M. [59] | |
Green Deal | 2021 | Digital Ecosystems for Developing Digital Twins of the Earth: The Destination Earth Case | Nativi, S. et al. [31] |
Cultural Heritage | 2022 | Populating the Data Space for Cultural Heritage with Heritage Digital Twins | Niccolucci, F. et al. [78] |
Mobility | 2022 | Enabling data spaces: Existing developments and challenges | Solmaz, G. et al. [79] |
Energy | 2022 | Supporting Energy Digital Twins with Cloud Data Spaces: An Architectural Proposal | Rucco, C. et al. [60] |
Cross-sector 1 | 2022 | Accessing spatial knowledge networks with maps | Jobst, M. and Gartner, G. [80] |
Sector | Publication Year | Title | Authors |
---|---|---|---|
Green Deal | 2023 | A Data Space for Climate Science in the European Open Science Cloud | Elia et al. [81] |
Sector | Publication Year | Title | Authors |
---|---|---|---|
Green Deal | 2023 | The role of the marine research infrastructures in the European marine observation landscape: present and future perspectives | Danobeitia et al. [82] |
Project Name | Start Year | Title |
---|---|---|
AD4GD | 2022 | All Data 4 Green Deal—An Integrated, FAIR Approach for the Common European Data Space |
FAIRiCUBE | 2022 | F.A.I.R. information cube |
interTwin | 2022 | An interdisciplinary Digital Twin Engine for science |
USAGE | 2022 | Urban Data Spaces for Green dEal |
Waterverse | 2022 | Water Data Management Ecosystem for Water Data Spaces |
B3 | 2023 | Biodiversity Building Blocks for policy |
EuroGEOSec | 2023 | Establishing the EuroGEO Secretariat to support the EuroGEO initiative |
Green.Dat.AI | 2023 | Energy-efficient AI-ready Data Spaces |
MoRe4nature | 2024 | Empowering citizens in collaborative environmental compliance assurance via MOnitoring, REporting and action |
Project Name | Start Year | Title | Sector |
---|---|---|---|
Circular TwAIn | 2022 | AI Platform for Integrated Sustainable and Circular Manufacturing | Industry |
Zero-SWARM | 2022 | ZERO-ENABLING SMART NETWORKED CONTROL FRAMEWORK FOR AGILE CYBER PHYSICAL PRODUCTION SYSTEMS OF SYSTEMS | Industry |
AI REDGIO 5.0 | 2023 | Regions and (E)DIHs alliance for AI-at-the-Edge adoption by European Industry 5.0 Manufacturing SMEs | Industry |
DaCapo | 2023 | Digital assets and tools for Circular value chains and manufacturing products | Industry |
FLEX4RES | 2023 | DATA SPACES FOR FLEXIBLE PRODUCTION LINES AND SUPPLY CHAINS FOR RESILIENT MANUFACTURING | Industry |
AUTO-TWIN | 2022 | Digital Twin generation, operations, and maintenance in circular value chains | Industry |
interTwin | 2022 | An interdisciplinary Digital Twin Engine for science | Green Deal |
Green.Dat.AI | 2023 | Energy-efficient AI-ready Data Spaces | Green Deal |
ENERSHARE | 2022 | European commoN EneRgy dataSpace framework enabling data sHaring-driven Across- and beyond-eneRgy sErvices | Energy |
OMEGA-X | 2022 | Orchestrating an interoperable sovereign federated Multi-vector Energy data space built on open standards and ready for GAia-X | Energy |
ENPOWER | 2023 | Energy Activated Citizens and Data-Driven Energy-Secure Communities for a Consumer-Centric Energy System | Energy |
TwinEU | 2024 | Digital Twin for Europe | Energy |
eBRAIN-Health | 2022 | eBRAIN-Health—Actionable Multilevel Health Data | Health |
ReNEW | 2022 | Resilience-centric Smart, Green, Networked EU Inland Waterways | Mobility |
BatteReverse | 2023 | A next-generation automated, connected, and standardised process for increased safety, efficiency, and sustainability of Li-ion BATTEry REVERSE logistics | Mobility |
COBALT | 2023 | Certification for Cybersecurity in EU ICT using Decentralized Digital Twinning | Security |
Project Name | Start Year | Title | Sector |
---|---|---|---|
BY-COVID | 2021 | Beyond COVID | Health |
eBRAIN-Health | 2022 | eBRAIN-Health—Actionable Multilevel Health Data | Health |
EOSC4Cancer | 2022 | A European-wide foundation to accelerate Data-driven Cancer Research | Health |
AD4GD | 2022 | All Data 4 Green Deal—An Integrated, FAIR Approach for the Common European Data Space | Green Deal |
interTwin | 2022 | An interdisciplinary Digital Twin Engine for science | Green Deal |
MoRe4nature | 2024 | Empowering citizens in collaborative environmental compliance assurance via MOnitoring, REporting and action | Green Deal |
TANGO | 2022 | Digital Technologies ActiNg as a Gatekeeper to information and data flOws | Security |
FAIR-IMPACT | 2022 | Expanding FAIR Solutions across EOSC | Cross |
DATAMITE | 2023 | DATA Monetization, Interoperability, Trading & Exchange | Cross |
EXA4MIND | 2023 | EXtreme Analytics for MINing Data spaces | Cross |
EOSC Beyond | 2024 | EOSC Beyond: advancing innovation and collaboration for research | Cross |
NOUS | 2024 | A catalyst for EuropeaN ClOUd Services in the era of data spaces, high-performance and edge computing | Cross |
Project Name | Start Year | Title | Sector |
---|---|---|---|
eBRAIN-Health | 2022 | eBRAIN-Health—Actionable Multilevel Health Data | Health |
DT-GEO | 2022 | A Digital Twin for GEOphysical extremes | Green Deal |
interTwin | 2022 | An interdisciplinary Digital Twin Engine for science | Green Deal |
Blue-Cloud 2026 | 2023 | A federated European FAIR and Open Research Ecosystem for oceans, seas, coastal and inland waters | Green Deal |
Article EC Initiative Project (ID) | Year | Service Level | Service Name | Specification of Technical Building Blocks | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
T1. Interoperability | T2. Sovereignty | T3. Value Creation | ||||||||||
Data Model | Data Exchange | Provenance Traceability | Access Usage | Identity | Trust Framework | Metadata | Publish Discover | Value-Added | ||||
Nativi, S. et al. [31,64,87] | 2021 | PaaS | DestinE Service Platform (DESP) | OpenAPI | OAuth, SAML | IAM (Keycloak) OpenID Connect | SIMPL | Marketplace | ||||
DaaS | DestinE Data Lake (DEDL) | Harmonised Data Access (HDA) OpenAPI | OpenID Connect | STAC | STAC, HDA OpenAPI | Big Data Processing | ||||||
PaaS | GEOSS Platform | Domain Ontology Model | REST | ISO 19115-2 [88] | OpenSearch | CoreTrustSeal, Nestor Seal, ISO 16363 [89] | ISO 19115 [90] | GEO Discovery and Access Broker (DAB) | GEOSS Portal (ESA) | |||
Elia et al. [81] | 2023 | PaaS | ENES Data Space Portal | CF Convention | NetCDF, REST | OAuth2, AAI (EGI) | AAI (EGI) | CMIP6 | Earth System Grid Federation (ESGF) Catalogue, CMIP6 | Marketplace (EOSC) | ||
Copernicus [85] | 2023 | PaaS | Copernicus Data Space Ecosystem (CDSE) | OData, REST | OpenAPI | OpenSearch | OpenID Connect | S3 Credentials (AWS) | STAC | STAC, OpenSearch Catalogue | Sentinel Hub, openEO, JupyterLab | |
INSPIRE [86] | 2022 | PaaS | INSPIRE Geoportal (GeoNetwork) | INSPIRE Data Models | OGC (WFS, WCS, SOS, STA), REST | AAA (ARE3NA) | AAA (ARE3NA) | INSPIRE Re3gistry | ISO 19139 [91], (Geo)DCAT-AP | CSW ISO AP, GeoNetwork | INSPIRE Knowledge Base | |
AD4GD (101061001) [92] | 2022 | PaaS | AD4GD Data Space | Darwin Core, SAREF, Smart Data Models, CF, GCOS ECVs, GEO BON EBVs, RAINBOW | OGC Data Exchange Toolkit, JSON-LD, SPARQL, SensorThings API (STA), REST | OGC API Records, W3C PROV-O | IAM (Keycloak) | IAM (Keycloak) | IDS, EDC Connectors | ISO 19115 [90] (Geo)DCAT | GeoNetwork Catalogue | Green Deal Information Model |
AquaINFRA (101094434) [93] | 2023 | PaaS | AquaINFRA Interactive Platform (AIP) | Water Ontology, ISO/TC 211 [94] | OGC APIs | OGC API Records | EOSC AAI | EOSC AAI | CKAN | OGC CWS, CKAN Catalogue | Marketplace (EOSC) | |
ASPECT (101081460) [95] | 2023 | SaaS DaaS | Seamless Climate Information System | CF Convention, WMO GRIB | NetCDF, GRIB | ESGF, MARS | ESGF | ISO, INSPIRE | ESGF, MARS | Climate Data Store, C3S | ||
B3 (101059592) [96] | 2023 | SaaS | Occurrence Cube | Darwin Core, CF Convention | NetCDF, RDF, JSON-LD, OWL, REST | GBIF Registry, GEO BON Registry | GBIF Registry GEO BON Registry | CoreTrustSeal | Ecological Metadata Language (EML), DataCite | GBIF Catalogue, GEO BON EBV Catalogue | GBIF Portal, EBV Data Portal | |
Blue-Cloud 2026 (101094227) [97] | 2023 | PaaS | Blue-Cloud Open Science Platform | NERC | EUDAT | W3C PROV | AAI (EGI) | IAM (Keycloak) | ISO 19115 [90], ISO 19139 [91], DCAT | DAB, CKAN Catalogue | Marketplace (EOSC) | |
DT-GEO (101058129) [98] | 2022 | PaaS | DT-GEO Platform | Common European Research Information Format | COMPSs | FENIX AAI | FENIX AAI | FAIR EVA Tool | EPOS ICS-C Metadata Catalogue | Marketplace (EOSC) | ||
EDITO-Infra (101101473) [99] | 2022 | PaaS | EDITO Platform | IAM (Keycloak), OAuth2 | IAM (Keycloak), OpenID Connect | Traefik | EDITO Catalogue | Marketplace | ||||
EDITO-Infra (101101473) [99] | 2022 | DaaS | EDITO Data Lake | CF Convention, Darwin Core, WoRMS, EUNIS | OGC APIs, NetCDF | STAC | STAC, Resto | DestinE Data Lake | ||||
EDITO-Model Lab (101093293) [100] | 2023 | SaaS | Virtual Ocean Model Lab (VOML) | CMEMS, EDITO Engine | ||||||||
ENVRI-Hub NEXT (101131141) [101] | 2024 | PaaS | ENVRI-Hub | WMO ECVs | AAI (EGI) | AAI (EGI) | ENVRI Catalogue | Marketplace (EOSC) | ||||
FAIR-EASE (101058785) [102] | 2022 | PaaS | Earth Analytical Lab (EAL) | NERC, INSPIRE, Global Change Master Directory, Darwin Core, WoRMS | OGC APIs, REST, SPARQL, NetCDF, OWL, RDF | W3C PROV-O | AAAI | AAAI | ISO 19115 [90], ISO 19139 [91], DCAT, EML | DAB | Marketplace (EOSC) | |
FAIRiCUBE (101059238) [103] | 2022 | PaaS | FAIRiCUBE HUB | INSPIRE | OGC APIs, REST, NetCDF | W3C PROV-PRIMER | IAM (Keycloak) | IAM (Keycloak) OpenID Connect | S3 Credentials (AWS) | STAC, ISO 19115 [90], DCAT, INSPIRE | STAC Catalogue | Marketplace |
Green.Dat.AI (101070416) [104] | 2023 | PaaS | GREEN.DAT.AI Platform | IDS Vocabulary Hubs | OGC STA, RDBS-O | IAM (Keycloak) | IAM (Keycloak) | Trusted Execution Environments (TEEs) | IDS Metadata Broker (Sovity), EDC Connector | AI Services Toolbox for Data Spaces | ||
ILIAD (101037643) [105] | 2022 H2020 | PaaS | ILIAD DTO Platform | Ocean Information Model | OGC APIs, REST, SDKs, Distributed Data Access Protocols | UNESCO Ocean Best Practices System (OBPS) | OAuth2 | X509, identity4EO (DEIMOS) | (Geo) DCAT-IP | NEXTGEOSS DataHub Catalogue | Iliad Marketplace | |
iMagine (101058625) [106] | 2022 | PaaS | iMagine IT Platform | Darwin Core, WoRMS, FISHBase | NetCDF | Darwin Core Archive (DwC-A) | AAI (EGI) | AAI (EGI) | CoreTrustSeal | DwC-A | IMIS Catalogue | Marketplace (EOSC) |
IMMERSE (821926) [107] | 2018 | SaaS | NEMO | CF Convention, Ocean Model | NetCDF | CECILL Software Licence [108] | Copernicus CMEMS | |||||
interTwin (101058386) [109] | 2022 | PaaS | Digital Twin Engine (DTE) | CF Convention | NetCDF, HDF5, GRIB, Open Neural Network Exchange (ONNX) | W3C PROV-DM | AAI (EGI) | AAI (EGI) | SIMPL | STAC, ISO 19115 [90], INSPIRE | STAC Catalogue | Marketplace EOSC |
IRISCC (101131261) [110] | 2024 | IaaS | EOSC AAI (EGI) | EOSC AAI (EGI) | IRISCC Catalogue | Marketplace (EOSC) | ||||||
LandSeaLot (101134575) [111] | 2024 | SaaS DaaS | LandSeaLot Integration Labs (ILs) | NERC | Ocean Data View (ODV) ASCII, NetCDF | SeaDataNet Common Data Index (CDI) | SeaDataNet Metadata Services | SeaDataNet CDI | LandSeaLot Portal, EMODnet, Copernicus, DTO | |||
USAGE (101059950) [112] | 2022 | IaaS | USAGE Catalogue (GeoCat Live) | ISO 19131 [113], OASC MIM2 | OGC Data Exchange Toolkit | W3C PROV-O | ISO 19115 [90], (Geo)DCAT | GeoDCAT Catalogue | Marketplace | |||
Waterverse (101070262) [114] | 2022 | DaaS SaaS | Water Data Management Ecosystem (WDME) | Water Ontology, Smart Data Models | NGSI-LD Context Broker, JSON-LD | Blockchain | Identity Access Tool, OAuth2 | Identity Access Tool | WDME Tools (FIWARE) | DCAT-AP, Dublin Core, DataCite | CKAN Catalogue | WDME Data Portal |
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Otsu, K.; Maso, J. Digital Twins for Research and Innovation in Support of the European Green Deal Data Space: A Systematic Review. Remote Sens. 2024, 16, 3672. https://doi.org/10.3390/rs16193672
Otsu K, Maso J. Digital Twins for Research and Innovation in Support of the European Green Deal Data Space: A Systematic Review. Remote Sensing. 2024; 16(19):3672. https://doi.org/10.3390/rs16193672
Chicago/Turabian StyleOtsu, Kaori, and Joan Maso. 2024. "Digital Twins for Research and Innovation in Support of the European Green Deal Data Space: A Systematic Review" Remote Sensing 16, no. 19: 3672. https://doi.org/10.3390/rs16193672
APA StyleOtsu, K., & Maso, J. (2024). Digital Twins for Research and Innovation in Support of the European Green Deal Data Space: A Systematic Review. Remote Sensing, 16(19), 3672. https://doi.org/10.3390/rs16193672