MOSAICrOWN | Multi-Owner data Sharing for Analytics and Integration respecting Confidentiality and Owner control

Summary
The application of data analysis techniques over large data collections provides great benefits, from the personal, to the business, research, and social domain. The availability of large data collections recording actions and choices of individuals and organisations can lead to great improvement in the understanding of how the world operates. The continuous evolution of ICT is enabling the realisation of such vision at a fast pace, supporting the realisation of architectures enabling collaborative data sharing and analytics. A clear obstacle towards the realisation of such potential and vision is represented by security and privacy concerns. Indeed, the (actual or perceived) loss of control over data and potential compromise of their confidentiality can have a strong detrimental impact on the realisation of an open framework for enabling the sharing of data from multiple independent data owners. The goal of MOSAICrOWN is to enable data sharing and collaborative analytics in multi-owner scenarios in a privacy-preserving way, ensuring proper protection of private/sensitive/confidential information. MOSAICrOWN will provide effective and deployable solutions allowing data owners to maintain control on the data sharing process, enabling selective and sanitised disclosure providing for efficient and scalable privacy-aware collaborative computations. MOSAICrOWN Consortium sees the participation of major industry players, providing strategic use cases with strong exploitation and impact, and of an SME supporting deployment and standardisation.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/825333
Start date: 01-01-2019
End date: 31-12-2021
Total budget - Public funding: 3 203 750,00 Euro - 3 203 750,00 Euro
Cordis data

Original description

The application of data analysis techniques over large data collections provides great benefits, from the personal, to the business, research, and social domain. The availability of large data collections recording actions and choices of individuals and organisations can lead to great improvement in the understanding of how the world operates. The continuous evolution of ICT is enabling the realisation of such vision at a fast pace, supporting the realisation of architectures enabling collaborative data sharing and analytics. A clear obstacle towards the realisation of such potential and vision is represented by security and privacy concerns. Indeed, the (actual or perceived) loss of control over data and potential compromise of their confidentiality can have a strong detrimental impact on the realisation of an open framework for enabling the sharing of data from multiple independent data owners. The goal of MOSAICrOWN is to enable data sharing and collaborative analytics in multi-owner scenarios in a privacy-preserving way, ensuring proper protection of private/sensitive/confidential information. MOSAICrOWN will provide effective and deployable solutions allowing data owners to maintain control on the data sharing process, enabling selective and sanitised disclosure providing for efficient and scalable privacy-aware collaborative computations. MOSAICrOWN Consortium sees the participation of major industry players, providing strategic use cases with strong exploitation and impact, and of an SME supporting deployment and standardisation.

Status

CLOSED

Call topic

ICT-13-2018-2019

Update Date

27-10-2022
Geographical location(s)
Structured mapping
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EU-Programme-Call
Horizon 2020
H2020-EU.2. INDUSTRIAL LEADERSHIP
H2020-EU.2.1. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
H2020-EU.2.1.1. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)
H2020-EU.2.1.1.0. INDUSTRIAL LEADERSHIP - ICT - Cross-cutting calls
H2020-ICT-2018-2
ICT-13-2018-2019 Supporting the emergence of data markets and the data economy
H2020-ICT-2019-2
ICT-13-2018-2019 Supporting the emergence of data markets and the data economy