Periodic Reporting for period 1 - GLACIATION (Green responsibLe privACy preservIng dAta operaTIONs)
Periodo di rendicontazione: 2022-10-01 al 2024-03-31
The GLACIATION project aims to enhance the efficiency and use of trustworthy digital technologies to meet the demands of citizens, industry, and public administrations concerning privacy, commercial and administrative confidentiality, as well as responsible, fair, and environmentally friendly data operations across the data lifecycle. To achieve this goal, GLACIATION aims to develop a novel Distributed Knowledge Graph (DKG) spanning the edge-core-cloud architecture and reducing energy consumption for data processing through Artificial Intelligence (AI) enforced minimal data movement operations.
More concretely, the project successfully submitted 14 out of 25 deliverables during the covered period, including technical reports, prototypes, research findings, and dissemination and exploitation strategies. Additionally, 5 out of 9 milestones were achieved, namely the initiation of scientific and technical work in each task and use case, the consolidation of the reference architecture, and the initiation of lab tests on sample of methods and use case data.
• A mechanism to deploy and operate a knowledge graph in a distributed cloud/edge/core environment, facilitating interoperability and supporting key platform objectives such as AI-enabled data movement, data privacy enforcement, and data analytics and visualisation.
• An AI/ML-enhanced workload orchestration engine to minimise energy consumption and data transfer latency to maximize processing performance across edge/cloud services.
• A controlled sharing of data within the GLACIATION platform across a range of services and providers while maintaining and enforcing data privacy requirements. The core component providing such controlled sharing ability will consist of a data agnostic policy language which annotates the privacy requirements of data.