Trustworthy, Energy-Aware federated DAta Lakes along the computing continuum.
TEADAL will enable the creation of trusted, verifiable, and energy-efficient data flows, both inside a data lake and across federated data lakes, based on a shared approach for defining, enforcing, and tracking data governance requirements with specific emphasis on privacy/confidentiality. The proposed stretched data lake, i.e., deployed in the continuum, will be based on an innovative control plane able to exploit all the controlled/owned resources, across clouds and at the edge, to improve data analysis.
The resulting capabilities of stretched data lakes also provide the essential basis for the creation of trustworthy mediatorless federations of data lakes to foster an effective data exchange among organizations while preserving privacy and confidentiality constraints without any imposed, and often not acceptable, third-party coordinator. Finally, by applying to data governance the principles of circular economy, i.e., to reuse data, application, and computation resources belonging to the data lake federation, will enable the creation of platforms for more sustainable data analytics.
Build efficient data lakes solutions with ease data handling across the computing continuum
TEADAL demonstrates a data lake control plane that handles the non-functional aspects of workloads across the computing continuum – automatically optimizes performance, enforces policies, run transformations, and secure the data paths, independently of the user code.
Construct trustworthy data lakes and mediatorless federation of data lakes
The TEADAL project enables the creation of trustworthy data lakes where privacy/confidentiality requirements are satisfied when handling data along the continuum as well as then shared among organizations.
Reduce the environmental impact of data analytics through energy-efficient federation of stretched data lakes
The TEADAL project aims to apply the principle of circular economy to the involved data (e.g., reducing data duplication, balancing data reuse and data accuracy, reduce the data movement) considering both design and operational levels.
Build privacy, organisational policies and GDPR compliant federation of stretched data lakes
The TEADAL project proposes a shared knowledge on the exact semantic of privacy/confidentiality requirements and how they are enforced, to avoid erroneous (different) interpretations that will lead to a break of the trust established between the federated data lakes.
Contribute to and influence European research and initiatives with an aim to improve data sharing
The TEADAL project aims to gather feedback, explore problems beyond the ones identified by partners, and to provide to such stakeholders concrete demonstrator of key innovations that the project will develop and to disseminate the resulting innovative approaches to improve trustworthy data sharing in Europe.