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Project

RAISE

RAISE aims at promoting a transparent way of sharing and processing data, enabling the research community to publish their work with evidence-based authenticity of the dataanalysis performed, ensuring at the same time the accreditation of their work. It provides the infrastructure for a distributed crowdsourced data processing system, moving from open data to open access data for processing, and a mechanism for sending the algorithm to the dataset instead of sending the data to the algorithm. 
The mission of RAISE is to provide the infrastructure for a distributed crowdsourced data processing system, moving from open data to open access data for processing. RAISE will provide the mechanism for sending the algorithm to the dataset instead of sending the data to the algorithm. The real value of open data for the research community is not to access them but to process them as conveniently as possible in order to reduce time-to-result and increase productivity.

RAISE aims at promoting a transparent way of sharing and processing data, enabling the research community to publish their work with evidence-based authenticity of the dataanalysis performed, ensuring at the same time the accreditation of their work. RAISE will be grounded on the fundamental principle defined in the FAIR Guiding Principles for scientific data management and stewardship (Findability, Accessibility, Interoperability and Reusability).

To do so, RAISE brings the processing algorithm (small size) to the dataset (large size) instead of downloading the dataset to the computer where the processing algorithm is. To increase the processing capacity of the dataset repositories, RAISE borrows the crowdsourcing concept where researchers can easily integrate in the existing workflows computers serving both their datasets and the processing capacity.

RAISE will produce the following Outputs:

  1. A trustworthy crowdsourced network of RAI Certified nodes offering data storing and processing resources
  2. The RAI Cloud platform to orchestrate the data sharing, processing and finding.
  3. The Research Analysis Identifier ? RAI , a unique identifier of any result along with the dataset information and the processing script, without disclosing any source code or raw data.
  4. Dataset plagiarism identification and dataset proof-of-origin services, to maximise the level of trust of the RAISE system.
  5. The RAI Synthetic Data Generator
 
  • Project ID:
    101058479
  • Start date:
    Oct 1, 2022
  • Duration:
    40 months
  • Funding:
    4 836 125,00 Euros