Created page with "==EU Project short name::DataCloud== ===EU Project full name::Open Autonomous programmable cloud appS & smart EdgE Sensors=== '''Full project details (EU Research results portal):''' CORDIS URL::https://cordis.europa.eu/project/id/101092702 === '''Project description:''' === The massive increase in device connectivity and generated data has resulted in the proliferation of intelligent processing services to create insights and exploit data in a multi-modal m..."
 
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==[[EU Project short name::DataCloud]]==
==[[EU Project short name::DataCloud]]==
===[[EU Project full name::Open Autonomous programmable cloud appS & smart EdgE Sensors]]===
===[[EU Project full name::ENABLING THE BIG DATA PIPELINE LIFECYCLE ON THE COMPUTING CONTINUUM]]===
'''Full project details (EU Research results portal):''' [[CORDIS URL::https://cordis.europa.eu/project/id/101092702]]
'''Full project details (EU Research results portal):''' [[CORDIS URL::https://cordis.europa.eu/project/id/101016835]]


=== '''Project description:''' ===
=== '''Project description:''' ===
The massive increase in device connectivity and generated data has resulted in the proliferation of intelligent processing services to create insights and exploit data in a multi-modal manner. Currently, the most powerful data processing operates in a centralized manner at the cloud, which provides the ability to scale and allocate resources on demand and efficiently. Centralized processing and cloud hosting, bound and limit their services and applications to operate in a resource restricted manner, relying usually on large single entities to provide, i) Authentication, ii) Data storage, iii) Data processing, iv) Connectivity, v) Vendor-locked environments for development and orchestration. This significantly limits the user from its data governance and even identity management. Similarly, existing solutions for edge device authentication require a centralized entity to trust them and authenticate them, rendering a non-portable identification paradigm. OASEES aims to create an open, decentralized, intelligent, programmable edge framework for Swarm architectures and applications, leveraging the Decentralized Autonomous Organization (DAO) paradigm and integrating Human-in-the-Loop (HITL) processes for efficient decision making. The OASEES vision is to provide the open tools and secure environments for swarm programming and orchestration for numerous fields, in a completely decentralized manner. An important aspect in this process is identification and identity management, in which OASEES targets the implementation of a portable and privacy preserving ID federation system, for edge devices and services, with full compliance and compatibility to GAIA-X federation and IDSA trust directives and specifications. This situation solidifies the need for an integrated enabler framework tailored to the edge’s extreme data processing demands, using different edge accelerators, i.e. GPU, NPU, SNN and Quantum.
DataCloud provides a novel paradigm covering the complete lifecycle of managing Big Data pipelines through discovery, design, simulation, provisioning, deployment, and adaptation across the Computing Continuum. Big Data pipelines in DataCloud interconnect the end-to-end industrial operations of collecting pre-processing and filtering data, transforming and delivering insights, training simulation models, and applying them in the cloud to achieve a business goal. DataCloud delivers a toolbox of new languages, methods, infrastructures, and prototypes for discovering, simulating, deploying, and adapting Big Data pipelines on heterogeneous and untrusted resources. DataCloud separates the design from the run-time aspects of Big Data pipeline deployment, empowering domain experts to take an active part in their definitions. The main exploitation targets the operation and monetization of the toolbox in European markets, and in the Spanish-speaking countries of Latin America. Its aim is to lower the technological entry barriers for the incorporation of Big Data pipelines in organizations’ business processes and make them accessible to a wider set of stakeholders regardless of the hardware infrastructure. DataCloud validates its plan through a strong selection of complementary business cases offered by SMEs and a large company targeting higher mobile business revenues in smart marketing campaigns, reduced production costs of sport events, trustworthy eHealth patient data management, and reduced time to production and better analytics in Industry 4.0 manufacturing. The balanced consortium consists of 11 partners from eight countries. It has three strong university partners specialised in Big Data, distributed computing, and high-productivity languages, led by a research institute. DataCloud gathers six SMEs and one large company (as technology providers and stakeholders/users/early adopters) that prioritise the business focus of the project in achieving high business impacts.


'''EuroVoc IDs:''' [[EuroVoc ID::/engineering and technology/electrical engineering, electronic engineering, information engineering/electronic engineering/computer hardware/quantum computers]]
'''EuroVoc IDs:''' [[EuroVoc ID::/medical and health sciences/health sciences/health care services/eHealth]]


'''EU Programme:'''
'''EU Programme:'''
[[Programme::Horizon Europe]]
[[Programme::Horizon Europe]]

Revision as of 12:02, 21 October 2025

DataCloud

ENABLING THE BIG DATA PIPELINE LIFECYCLE ON THE COMPUTING CONTINUUM

Full project details (EU Research results portal): https://cordis.europa.eu/project/id/101016835

Project description:

DataCloud provides a novel paradigm covering the complete lifecycle of managing Big Data pipelines through discovery, design, simulation, provisioning, deployment, and adaptation across the Computing Continuum. Big Data pipelines in DataCloud interconnect the end-to-end industrial operations of collecting pre-processing and filtering data, transforming and delivering insights, training simulation models, and applying them in the cloud to achieve a business goal. DataCloud delivers a toolbox of new languages, methods, infrastructures, and prototypes for discovering, simulating, deploying, and adapting Big Data pipelines on heterogeneous and untrusted resources. DataCloud separates the design from the run-time aspects of Big Data pipeline deployment, empowering domain experts to take an active part in their definitions. The main exploitation targets the operation and monetization of the toolbox in European markets, and in the Spanish-speaking countries of Latin America. Its aim is to lower the technological entry barriers for the incorporation of Big Data pipelines in organizations’ business processes and make them accessible to a wider set of stakeholders regardless of the hardware infrastructure. DataCloud validates its plan through a strong selection of complementary business cases offered by SMEs and a large company targeting higher mobile business revenues in smart marketing campaigns, reduced production costs of sport events, trustworthy eHealth patient data management, and reduced time to production and better analytics in Industry 4.0 manufacturing. The balanced consortium consists of 11 partners from eight countries. It has three strong university partners specialised in Big Data, distributed computing, and high-productivity languages, led by a research institute. DataCloud gathers six SMEs and one large company (as technology providers and stakeholders/users/early adopters) that prioritise the business focus of the project in achieving high business impacts.

EuroVoc IDs: /medical and health sciences/health sciences/health care services/eHealth

EU Programme: Horizon Europe