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H2020

AICHAIN

A platform for privacy-preserving Federated Machine Learning using Blockchain to enable Operational Improvements in ATM

Programme
Horizon 2020
Started
Ends
Duration
30 months
Total cost
EUR 1,525,545
EU contribution
EUR 996,505
Participants
7 from 5 countries
Topic
H2020_SESAR-ER4-04-2019
Grant agreement
894162

Coordinated by Sita Ewas Application Services SL (ESSpain).

Consortium

EU contribution per participant as the open data of CORDIS states it; for a participant with linked third parties it may include their share, and a participant whose amount the data does not hold or cannot make consistent shows Not stated. A participant who left the project is not listed; see the history below.

Members of the consortium
OrganisationCountryRoleEU contributionRecognised by
Sita Ewas Application Services SLESSpainCoordinatorEUR 283,407PIC (1.00)
Eurocontrol - European Organisation for the Safety of Air NavigationBEBelgiumParticipantEUR 0PIC (1.00)
Sita Onair Switzerland SarlCHSwitzerlandThird partyNot statedPIC (1.00)
Swiss International Air Lines AGCHSwitzerlandParticipantEUR 289,817PIC (1.00)
Nommon Solutions and Technologies SLESSpainParticipantEUR 202,500PIC (1.00)
Sita Information Networking Computing UK LimitedGBUnited KingdomThird partyNot statedPIC (1.00)
Scaleout SystemsSESwedenParticipantEUR 220,781PIC (1.00)

Changes of the consortium

First seen on with 7 participants from 5 countries.

A snapshot of each project's members is taken once a month; a change is recorded when a snapshot differs from the one before. A project with no change listed has had the same members since it was first observed.

Project page on CORDIS (opens in new tab)

Where this comes from

EU contribution is the amount CORDIS's open data pays to the participant. For a participant with linked third parties it may include their share (the CORDIS page prints the net); an amount the data does not hold is left out, not counted as zero. EDF factsheets state none per participant, so EDF projects count as projects but add nothing to the amounts.

Organisation-level facts only: a name, a country, a role, an amount, a year. A participant is recognised by its PIC where the source gives one, otherwise by name; the page says which. How the data is built.