VesselAI Digital Platform Delivered.
| 🚢 Excited to highlight the VesselAI platform - an open-source maritime analytics platform designed to support the full data and innovation lifecycle in shipping. 📊 VesselAI brings together data ingestion, storage, exploration, SQL analytics, ETL, AI services, workflow orchestration, and digital twin capabilities in one integrated environment. This allows users to move from raw maritime data to actionable insights for vessel performance analysis, operational optimization, and environmental and economic assessment. 🤖 The platform supports advanced AI and machine learning workflows, including notebook environments, AI models, AI agents, and workflow management tools, while also enabling digital twin applications such as vessel and retrofit analysis, voyage planning, and optimization. 🔐 In a sector where access to maritime data is often limited, VesselAI helps enable more open, secure, and collaborative innovation through federated data sharing, encryption mechanisms, and semantic interoperability across systems. 🌍 By supporting academia, research, and industry stakeholders, VesselAI contributes to a stronger digital ecosystem for smarter, greener, and more efficient shipping. |
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User Manual for VesselAI Platform
🚢 We are pleased to share – VesselAI User Manual
📘 This public deliverable provides a structured overview of the VesselAI platform, presenting its core components, functionalities, and main user workflows. The manual explains how the platform supports the full maritime data lifecycle, from data ingestion and storage to data exploration and analysis, processes, data streaming, data governance, AI services, workflow orchestration, and digital twin (DT) and decision support system (DSS) capabilities. It is designed to help users transform raw maritime data into actionable insights for vessel performance analysis, operational optimization, and environmental and economic assessment.
⚓ In a sector where digital platforms are often proprietary and access to data is restricted, wider collaboration and innovation can be difficult. Limited data sharing reduces opportunities for research communities and R&D partners to validate AI and machine learning methods on critical maritime datasets. In this context, TwinShip will further strengthen its DT/DSS framework by leveraging the VesselAI digital platform, originally developed through the collaborative VesselAI H2020 project.
🔐 As an open-source platform with a sophisticated architecture for large-scale data processing and advanced AI/ML applications, VesselAI is designed to support secure and seamless data sharing in the maritime sector. It introduces a federated data space with dedicated encryption mechanisms for maritime data, while also promoting semantic interoperability through shared vocabularies and ontologies, enabling a common understanding of exchanged data across different systems.
🌍 With implementations already in place at ICCS and DSSLab in Athens, and an upcoming setup at UiT in Tromsø, the platform is expanding its reach and value for academia, research, and industry stakeholders. This also strengthens resilience through a data backup strategy aligned with the 3-2-1 Rule.
👏 A big thank you to all partners and contributors involved in this work.
Now you download the deliverable from: https://www.researchgate.net/publication/403268274_User_Manual_for_VesselAI_Platform
TWINSHIP ONTOLOGY
| 🚢 Exciting milestone for the TwinShip Consortium project! 🔗 https://ontology.twin-ship.eu/index-en.html We're thrilled to announce the publication of the first version of the TwinShip Ontology - a foundational step toward standardizing the digital twin in shipping. 🌐 A significant portion of these ontologies is grounded in the IMO Compendium - the internationally recognized framework designed to enable seamless, standardized communication between vessels and ports. By building on this foundation, we ensure our work aligns with the broader maritime ecosystem from day one. So, what does this mean in practice? While these ontologies are developed to support vessel Digital Twin (DT) model development, their impact extends far beyond a single project: ✅ Shipping companies can standardize data collection and processing across their fleets ✅ DT model development can follow a consistent, interoperable framework ✅ Applications like voyage optimization can be built on shared, reliable data structures What's next? The road ahead is equally exciting. Our next milestone is the development of knowledge graphs for the TwinShip pilot vessels - which will serve as the backbone for the actual DT model development to follow. The maritime industry is at the beginning of a digital transformation, and ontologies like these are the quiet infrastructure that will make it scalable, interoperable, and impactful. 👉 Explore the IMO Compendium: https://imocompendium.imo.org/public/IMO-Compendium/Current/index.htm We'd love to hear from maritime professionals, researchers, and technology partners - how is your organization approaching data standardization for digital twins? |
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TwinShip at the Port of Valencia
| Today, the TwinShip Horizon Europe project team visited the Port of Valencia to discuss future port needs and explore how our Digital Twin (DT) models and Decision Support System (DSS) tools can support next-generation, sustainable port operations. This collaboration is a key step toward aligning smart port development, decarbonization goals, and advanced maritime digitalization in future ports. |
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More Articles …
- Successful completion of the First Year of the TwinSip project
- The TwinShip futuristic vessel is charting its course toward the Ports of the Future!
- TwinShip Horizon Europe Project was presented at the AI Enables Cybersecurity: The Meetup event 2026
- TwinShip's 4th Pilot Demonstration Sets Sail Toward Net Zero - TwinShip Futuristic Vessel Concept - Maritime Digital Twin
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