OpenMaker brings together mainstream manufacturers and makers (i.e. tech-savvy craftsmen driven by social innovation and open source principles) in an purposely designed ecosystem built to enable cross-boundary partnerships for innovation. The partnerships will be facilitated by a targeted programme piloted in four locations in Europe and curated by experienced facilitators. Combining skills and expertise across boundaries will benefit all collaborators and stimulate innovation in manufacturing. Specifically, in relation to business models, production processes, products and governance structure and systems. This is intended to contribute to industrial renewal in Europe which will have direct benefits for sustained growth and employment. This bespoke ecosystem will blend on and offline opportunities for collaboration mirroring the multifaceted ways individuals interact in a networked society. Our dedicated digital platform will support communication between all the partners in the four locations and allow stakeholders and partners from other locations to participate. It will also function to map and collect data on social dynamics. Network analysis will be used to harvest data, and generate a deeper understanding of the social dynamics between the partners and across the stakeholders which constitute this community. Such knowledge will help the consortium to improve methods and tools to foster partnerships for innovation in manufacturing. This project will benefit society through generating novel partnerships that combine greater productivity and social impact. Moreover it will provide evidence for business, policymakers and the public that industrial development can serve the common good while still being competitive and sustainable.

The cloud computing industry has grown massively over the last decade and with that new areas of application have arisen. Some areas require specialized hardware, which needs to be placed in locations close to the user. User requirements such as ultra-low latency, security and location awareness are becoming more and more common, for example, in Smart Cities, industrial automation and data analytics. Modern cloud applications have also become more complex as they usually run on a distributed computer system, split up into components that must run with high availability. Unifying such diverse systems into centrally controlled compute clusters and providing sophisticated scheduling decisions across them are two major challenges in this field. Scheduling decisions for a cluster consisting of cloud and edge nodes must consider unique characteristics such as variability in node and network capacity. The common solution for orchestrating large clusters is Kubernetes, however, it is designed for reliable homogeneous clusters. Many applications and extensions are available for Kubernetes. Unfortunately, none of them accounts for optimization of both performance and energy or addresses data and job locality. In DECICE, we develop an open and portable cloud management framework for automatic and adaptive optimization of applications by mapping jobs to the most suitable resources in a heterogeneous system landscape. By utilizing holistic monitoring, we construct a digital twin of the system that reflects on the original system. An AI-scheduler makes decisions on placement of job and data as well as conducting job rescheduling to adjust to system changes. A virtual training environment is provided that generates test data for training of ML-models and the exploration of what-if scenarios. The portable framework is integrated into the Kubernetes ecosystem and validated using relevant use cases on real-world heterogeneous systems.

EWOC project aims at developing a novel converged optical wireless network solution relying on a flexible, virtualizable infrastructure, required for full resource optimisation beyond 5G (B5G) requirements. Fundamental innovation will be sought through merging of the enabling concepts of optical layer virtualization, high frequency mm-wave transmission, multiple antenna technology, cell densification, terra-over-fiber (ToF) based femtocell connectivity and cloud radio access network (C- RAN) architecture. EWOC will aim at high capacity, low latency communications (40-90 GHz frequency), providing the basis for a 50-fold improvement over the 5G baseline. This necessitates development of novel, femto-cell technology, and seamless coexistence with first round legacy deployment. Such scenario also requires novel channel models and simulation methodologies to attain the desired trade-off between coverage, throughput and densification limits. EWOC will rely on fiber-optic deployment towards ToF connectivity, as an “added on feature” for the C-RAN architecture supporting resource management of versatile services with varying demands. Scenario compliant optical fronthaul virtualisation techniques, designed to provide cost effective beyond state-of-the-art resource optimisation, will be pursued through novel optical transceiver schemes and software defined network-based digital signal processing techniques. Research and training disciplines will serve as building blocks towards the scientific and socio-economic goals of increased capacity, coverage, flexibility, spectral efficiency, cost effectiveness, vendor agnosticism, and upgradability. EWOC provides a framework for promotion of such interdisciplinary innovation, with strong interoperability of models and methodologies from different disciplines. As such, EWOC training network is designed to foster opportunities for scientific and professional growth of ESRs from both topical and inter-disciplinary standpoints.

Femme Forward is a forward-looking project targeting the low representation of women in digital jobs and start-ups. Through an innovative and comprehensive training programme, women with various backgrounds will be empowered to either start a career in tech or employ their experience and knowledge to set up a tech start-up. The Femme Forward consortium is a partnership of 15 stakeholders led by Simplon.co (SIMPLON.CO), bringing together key industry, technology and education stakeholders in Europe. Each participant in the project has a well-defined role and contributes to achieving a qualitative and comprehensive partnership. The consortium will work to identify, develop and pilot high-quality digital education content that will tackle the current gender gap in the digital economy, enabling at least 500 women to start on the track to tech employment or entrepreneurship. The project will be delivered across 8 interconnected work packages, during which 23 outputs will be delivered over 24 months.Femme Forward will support women with various backgrounds with a special focus on: migrants and refugees whose qualifications are not recognized in the EU; professionals and women who want to change careers for better job prospects; young graduates from non-tech degrees who want to move into tech positions; women who have a tech business idea and want to make it a reality; women re-entering the labor market after maternity, etc.At the end of the project, we will have created an easy to use and extensive repository of tested, high-quality educational materials, available in multiple languages, and on a multi-device compatible learning platform.

Global Systems Science – GSS – is an emerging research field focused on the risks and opportunities involved in global coordination problems. Examples of global systems include the internet, financial markets, intellectual property rights, global energy use and others. Developing evidence and understanding in view of such systems and of related policies is rapidly becoming a vital challenge for modern societies. It requires capabilities for transdisciplinary work that cannot be mastered without massive use of ICT. By the nature of the problem, the relevant datasets are mostly very big, including data streams from social medi. To make things more complicated, the relevant algorithms do require the power of high-performance computing. High Performance Data Analysis (HPDA) is the key to success for GSS! A key contribution of the Center of Excellence for Global Systems Science – COEGSS – will be the development of an HPC-based framework to generate customized synthetic populations for GSS applications. By blending GSS and HPC, we will be able to provide decision makers and civil society with real-time assessments of global risks and opportunities as well as with essential background knowledge about them. This will enable the HPC industry to supply hard- and software for applications well beyond the issues to which HPC has been dedicated so far.