The DIGITbrain project aims to enable customised industrial products and to facilitate cost-effective distributed and localised production for manufacturing SMEs, by means of leveraging edge-, cloud- and HPC-based modelling, simulation, optimisation, analytics, and machine learning tools and by means of augmenting the concept of digital twin with a memorising capacity towards a) recording the provenance and boosting the cognition of the industrial product over its full lifecycle, and b) empowering the network of DIHs to implement the smart business model "Manufacturing as a Service".
The EOSC-hub project creates the integration and management system of the future European Open Science Cloud that delivers a catalogue of services, software and data from the EGI Federation, EUDAT CDI, INDIGO-DataCloud and major research e-infrastructures. This integration and management system (the Hub) builds on mature processes, policies and tools from the leading European federated e-Infrastructures to cover the whole life-cycle of services, from planning to delivery.
The mission of CloudiFacturing is to optimize production processes and producibility using Cloud/HPC-based modelling and simulation, leveraging online factory data and advanced data analytics, thus contributing to the competitiveness and resource efficiency of manufacturing SMEs, ultimately fostering the vision of Factories 4.0 and the circular economy. CloudiFacturing will empower over 60 European organizations (many of them being manufacturing SMEs) and will support about 20 cross-national application experiments that will primarily be selected via two Open Calls.
Define a generic pluggable framework, called MiCADO (Microservices-based Cloud Application-level Dynamic Orchestrator) that supports optimal and secure deployment and run-time orchestration of cloud applications. The project will provide a reference implementation of this framework by customising and extending existing, typically open source solutions. Moreover, it will demonstrate via large scale close to operational level SME and public sector demonstrators the applicability and impact of the solution.
Existing research mostly focuses on pre-optimising algorithms, which are not applicable to already available VM images. With its VM synthesiser, ENTICE will extend pre-optimising approaches so that image dependency descriptions are mostly automatically generated. The project will also introduce new comprehensive post-optimising algorithms so that existing VM images can be automatically adapted to dynamic Cloud environments.
The Agrodat.hu project aims to establish an agricultural knowledge centre and decision support system based on data gathered by an innovative, complex sensor system and from international open repositories. The new research infrastructure and service platform rely on big data, cloud, and HPC technologies to support precision farming.
The CloudSME project will develop a cloud-based, one-stop-shop solution providing a scalable platform for small or larger scale simulations, and enable the wider take-up of simulation technologies in manufacturing and engineering SME’s. The CloudSME Simulation Platform will support end user SME’s to utilise customized simulation applications in the form of Software-as-a-Service (SaaS) based provision.
Main objective is to involve and engage in long-term significantly more citizens and new communities in the volunteer and private (campus-wide or enterprise) Distributed Computing Infrastructures by supporting the rapid creation, efficient operation, and dynamic expansion of this type of DCIs for e-Science. Coordinate and synchronise the dissemination and support activities of major European stakeholders of volunteer and Desktop Grids with focus on the International Desktop Grid Federation.
The SCI-BUS project aims to ease the life of e-Scientists by creating a new science gateway customisation methodology based on the generic-purpose gUSE/WS-PGRADE portal family. The customised science gateways will enable scientists to focus on their work and exploit resources of main Distributed Computing Infrastructures (DCIs) without the need to deal with the underlying infrastructures' details.