ExpertiseUpdated on 16 May 2025
Data Spaces and GAIA-X
About
Marispace-X is a pioneering digital maritime data space designed to enhance data sovereignty, security, interoperability, and modularity within the maritime industry. As a Gaia-X project, it revolutionizes maritime big data processing by integrating sensor data across Edge, Fog, and Cloud Computing.
Marispace-X accelerates the digitalization of the Blue Economy
Field
- Data ecosystems
 
Organisation
Similar opportunities
Project cooperation
Circular quality assurance and assessment of remanufacturing
- Early idea
 - Consortium seeks Partners
 
Chris Schönekehs
Research Associate at WZL RWTH Aachen University
Aachen, Germany
Project cooperation
AI, Digital Twin & Data-Driven Solutions for Circular Value Creation
- Data technologies | Assistance and Expert systems
 - Enabling technologies | Network design of reverse supply chains
 - Data technologies | Design of an adaptable Digital Product Pass:
 - Enabling technologies | Robotic / handling - and assistance systems
 - Data technologies | (AI based) process and system control technologies
 - Enabling technologies | (Advanced) Materials and additive manufacturing
 - Data technologies | (AI based) Material and Product Design, Decomposition and Separation
 - Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
 - Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
 - Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
 - Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
 - Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
 - Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
 - Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
 - Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
 - Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
 - Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
 - Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
 - Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
 - Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
 
Süleyman Altınışık
Expert R&D Engineer at OBSS Technology
Istanbul, Türkiye
Expertise
- Data ecosystems
 - Industry 4.0 technologies
 - (AI based) recognition systems
 - Manufacturing and machine learning
 - (AI based) Material and Product Design
 - Simulation models and predictive analytics
 - (AI based) process and system control technologies
 
Laura Bies
Lab Lead Smart Quality at August-Wilhelm Scheer Institut
Saarbrücken, Germany