CyclOps

Automated end-to-end data life cycle management for FAIR data integration, processing and re-use

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CyclOps proposes a new framework for the governance and maintenance of the full data life cycle for large-scale data volumes generated in heterogeneous distributed sources to enable data sharing and exchange. The main contribution of CyclOps is an intelligent end-to-end automation of the data life cycle using knowledge graphs (KGs), ultimately improving operations. KGs are established formal models to represent data and metadata while providing context and guaranteeing interoperability, adhering to the FAIR Guiding Principles (Findability, Accessibility, Interoperability, and Reusability of data for machines and humans alike). CyclOps operationalizes the end-to-end data life cycle via a layered bottom-up approach and framework whereby: i) DataOps automates data management tasks, such as discovery, curation and quality, and integration; ii) AIOps provides a decentralised repository of AI algorithms, and makes the resulting AI models available; iii) a Data and execution abstraction layer facilitates the development of distributed data preprocessing and analysis, and iv) the Intent-based human interface provides a human-centric interface to automatically provide services to exchange, explore, visualise and integrate with data spaces, driving the automatic execution of analytical pipelines. The framework is overseen by v) the smart Data Governance and Trust, a transversal semantic layer that regulates the system, enforces data-related rights, obligations and responsibilities, such as the General Data Protection Regulation (GDPR) or the draft Artificial Intelligence Act, while enabling interoperability and guaranteeing the security and privacy of the system. The salient feature of CyclOps is its ability to empower organisations to seamlessly provide, cross and analyse data from and for data spaces, and facilitate the provision of added-value services.


Eurac will help to establish links with the Europen Green Deal Data Space and will implement one of the reference use cases targeting the development and implementation of an integrated climate risk management tool, building on the combination of earth observation processing through standardized means like openEO as well as graph-based querying in collaboration with the university of Bolzano.


Contact Person: alexander.jacob@eurac.edu

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