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R&I Project Hub

Waterverse

The WATERVERSE mission is to develop a Water Data Management Ecosystem (WDME) for making data management practices and resources in the water sector accessible, affordable, secure, fair, and easy to use, improving usability of data and the interoperability of data-intensive processes, thus lowering the entry barrier to data spaces, enhancing the resilience of water utilities and boosting the perceived value of data and therefore the market opportunities behind it.

enRichMyData

enRichMyData provides a novel paradigm for building rich, high-quality and valuable datasets to feed Big Data Aalytics and AI applications. The paradigm consists in facilitating the specification and scalable execution of data enrichment pipelines, with a focus on supporting various data enrichment operations such as discovery, understanding, selection, cleaning, transformation, integration of Big Data from a variety of sources.

NebulOus

In the realms of cloud and fog computing brokerage, it’s important to introduce advanced methods and tools. This is the aim of the EU-funded NebulOus project. NebulOus will enable secure and optimal application provisioning and reconfiguration over the cloud computing continuum. Specifically, it will develop a novel Meta Operating System and platform for enabling transient fog brokerage ecosystems that seamlessly exploit edge and fog nodes. This will be in conjunction with multi-cloud resources, to cope with the requirements posed by low latency applications

TEADAL

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.

SecOPERA

Security of open-source solutions in the business interconnected market (especially in IoT where a single product may include components from various Tier 1 or OEM manufacturers) is hard to assure. OEM SW/HW developers that employ open-source solutions must assume that any component provided by 3rd parties needs to be reassessed for security as there is no holistic security auditing/testing process to cover the full production line.

ORSHIN

The EU-funded ORSHIN project aims to build connected OSH devices, such as (I)IoT ones, taking advantage of unprecedented opportunities provided by open-source hardware. The project will specify a novel and dependable methodology to develop, maintain and decommission OSH devices which we call trusted life cycle. The project will research new formal verification models and tools to protect OSH devices from critical threats such as side-channel and fault injection vulnerabilities.

ENCRYPT

The deluge of big data, accompanied by developments in software and hardware technologies leveraging them, has created new opportunities for research and industry. Europe The main challenges, though, faced by researchers and service providers working with personal data, are stemming from the fact that these data need to be processed in a privacy-preserving way, as they contain sensitive information.

PAROMA-MED

The EU-funded PAROMA-MED project aims to develop novel technologies, tools, services and architectures for patients, health professionals, data scientists and health domain businesses so that they will be able to interact in the context of data and ML federations according to legal constraints and with complete respect to data owners’ rights from privacy protection to fine grained governance, without performance and functionality penalties of ML/AI workflows and applications.

HARPOCRATES

Availability of large volumes of user data combined with tailored statistical analysis present a unique opportunity for organizations across the spectrum to adapt and finetune their services according to individual needs. Having shown remarkable results in analyzing user data, machine learning models attracted global adulation and are applied in a plethora of applications including medical diagnostics, pattern recognition, and threat intelligence. However, such service improvements and personalization based on user data analysis come at the heavy cost of privacy loss.

CERTIFY

The Internet of Things (IoT) provides numerous business opportunities. However, it also comes with new challenges such as compromised security, heightening the importance of IoT infrastructure security management. In line with this, the EU-funded CERTIFY project will define a methodological, technological and organisational approach towards IoT security life cycle management. The project will also design and implement a cybersecurity life cycle management framework for IoT devices that will operate by gathering and sharing information both internally and externally.

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