The goal of NEARDATA is to create an extreme data infrastructure mediating data flows between Object Storage and Data Analytics platforms across the Compute Continuum.
Data Centric Computing
Type of asset:
To create and standardize secured methods to move and process exa-scale health data from the edge to the cloud. This data is highly confidential (health data) thus ensuring confidential transfers is a must as well as challenging.
Our novel XtremeDataHub platform is an intermediary data service that intercepts and optimises data flows (S3 API, stream APIs) with highperformance near-data connectors (Cloud/Edge). Finally, our unique Data Broker service will provide secure data access and orchestration of dispersed data sources thanks to TEEs and federated learning architectures.
To allow efficient distribution of health data to sequence the genome and better understand human DNA. Create generalised machine-learning models that can aid surgeons during surgery and allow video data to be analysed in real-time and with low latency. Expand the analysis of metabolomics raw data and boost external access and efficient re-use of open data.
Create a novel intermediary data service (XtremeDataHub) providing serverless data connectors that optimize data management operations (partitioning, filtering, transformation, aggregation) and interactive queries (search, discovery, matching, multi-object queries) to efficiently present data to analytics platforms. As a second novelty mechanisms to enable real-time streaming and processing of health data will be provided. Finally, a novel data broker service enabling trustworthy data sharing and confidential orchestration of data pipelines across the compute continuum will be created.
Open-source licenses and open-data repositories.
Universities, hospitals, health institutes, SME with expertise on security and confidentiality.
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