CyclOps Project
Enable trustworthy, interoperable data-driven innovation through intelligent governance, automated processing pipelines, and data space readiness.
Official Logo
Automated end-to-end data life cycle management for FAIR data integration processing and re-use
Project Details
Funded under: Horizon Europe
Project ID: 101135513
Start Day: 01/01/2024
Project Duration: 3 Years
Tags: Data Spaces, Trustworthy AI
Social Media
Learn more about this project
Let’s Work Together for Development
Let’s explore how we can support your next project.
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.
The Story
In today’s data-driven economy, integrating and governing data from heterogeneous sources is a key competitive advantage. Industries such as manufacturing, mobility, and tourism increasingly rely on AI applications to extract value from machine- and human-generated data.
Despite the European push for Common Data Spaces, end-to-end data lifecycle governance remains largely manual and fragmented, leading to data silos and limited interoperability.
CyclOps addresses this challenge through a unified framework for automated data lifecycle governance. By leveraging Knowledge Graphs and a human-in-the-loop approach, it enables systematic data ingestion, integration, and sharing, ensuring interoperability, FAIR compliance, and data sovereignty.
Project Overview
CyclOps proposes a novel governance framework designed to manage the entire data lifecycle across heterogeneous and distributed environments. Unlike existing solutions that focus on isolated aspects such as scalable storage, machine learning performance, explainability, or data sharing, CyclOps integrates governance as a core capability across all stages of the lifecycle.
At the heart of the framework lies the use of Knowledge Graphs (KGs), which serve as formal semantic models to represent data and metadata while preserving context. These models enable intelligent automation of data processing pipelines, ensuring interoperability and alignment with the FAIR Guiding Principles.
Through a human-in-the-loop approach, CyclOps automates the generation and execution of data workflows, reducing manual effort while maintaining oversight and trust. This enables organizations to seamlessly provide, combine, and analyze machine- and human-generated data across data spaces.
By enabling governed data sharing and exchange, CyclOps facilitates the development of new data-centric business models and value-added services across multiple industrial sectors.
Our Contribution
FDI leads the offset-printing manufacturing use case and plays a central role in transforming CyclOps innovations into deployable industrial solutions.
The Results
CyclOps establishes a governance-driven foundation for scalable, interoperable, and trustworthy data-centric AI systems.
Project’s Progress so far
