Register
Register
Register

Project cooperationUpdated on 15 May 2025

Looking for R&D Partners in AI-Driven Data Governance and Circular Ecosystems

emre ışık

Data & AI Solutions Lead at DIP BİLGİSAYAR YAZILIM TİCARET ANONİM ŞİRKETİ

İstanbul, Türkiye

About

At DIP Bilgisayar Yazılım Ticaret A.Ş., we are developing MetaWorks, a comprehensive data governance and analytics platform.
MetaWorks offers metadata management, data lineage, data quality scoring, masking, and GenAI-supported SQL generation – designed for enterprises aiming to manage data effectively and compliantly.

We are actively looking for project partners for Eureka, Horizon Europe, or other collaborative programs in areas such as:

  • Circular data ecosystems and semantic interoperability

  • AI-powered data preparation and impact analysis

  • Data compliance automation and digital product passports

  • Low-code platforms for data integration and transformation

We bring technical expertise and a robust platform to co-develop innovative solutions with shared value. Let's collaborate to unlock the future of smart and sustainable data ecosystems.

Stage

  • Already defined

Topic

  • 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.
  • Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
  • Data technologies | (AI based) process and system control technologies
  • Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
  • Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
  • Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
  • Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
  • 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 | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
  • Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)

Type

  • Consortium seeks Partners
  • Expertise offered

Organisation

Similar opportunities

  • Project cooperation

    Heat-as-a-service PLUS +

    • Early idea
    • Consortium seeks Partners
    • Data technologies | Design of an adaptable Digital Product Pass:
    • Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
    • Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
    • 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.

    Sina Herceg

    Scientist at Fraunhofer Institute for Solar Energy Systems

    Freiburg im Breisgau, Germany

  • Project cooperation

    Circular and Sustainable Transport Infrastructure

    • Early idea
    • Already defined
    • Expertise offered
    • Consortium seeks Partners
    • Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
    • Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
    • Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
    • Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
    • 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)

    Amir Garmabaki

    Associate Prof. at Luleå University of Technology

    Luleå, Sweden

  • Project cooperation

    Looking for a partner

    • Consortium seeks Partners
    • Data technologies | Design of an adaptable Digital Product Pass:
    • Enabling technologies | (Advanced) Materials and additive manufacturing
    • 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)
    • Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
    • 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.

    Kyra Sophie Rimrodt

    Fraunhofer Institute for Solar Energy Systems

    Freiburg im Breisgau, Germany