Despite an improved digital access to scientific publications in the last decades, the fundamental principles of scholarly communication remain unchanged and continue to be largely document-based. The document-oriented workflows in science have reached the limits of adequacy as highlighted by recent discussions on the increasing proliferation of scientific literature, the deficiency of peer-review and the reproducibility crisis. In ScienceGRAPH we aim to develop a novel model for representing, analysing, augmenting and exploiting scholarly communication in a knowledge-based way by expressing and linking scientific contributions and related artefacts through semantically rich, interlinked knowledge graphs. The model is based on deep semantic representation of scientific contributions, their manual, crowd-sourced and automatic augmentation and finally the intuitive exploration and interaction employing question answering on the resulting ScienceGRAPH base. Currently, knowledge graphs are still confined to representing encyclopaedic, factual information. ScienceGRAPH advances the state-of-the-art by enabling to represent complex interdisciplinary scientific information including fine-grained provenance preservation, discourse capture, evolution tracing and concept drift. Also, we will demonstrate that we can synergistically combine automated extraction and augmentation techniques, with large-scale collaboration to reach an unprecedented level of knowledge graph breadth and depth. As a result, we expect a paradigm shift in the methods of academic discourse towards knowledge-based information flows, which facilitate completely new ways of search and exploration. The efficiency and effectiveness of scholarly communication will significant increase, since ambiguities are reduced, reproducibility is facilitated, redundancy is avoided, provenance and contributions can be better traced and the interconnections of research contributions are made more explicit and transparent.

The semiconductor industry is characterised by complex supply chain structures. A common language and structure has to be developed and enrolled to enable smooth collaboration among different supply chain participants in this B2B (business to business) environment. SC³ relies on enabling a collaboration of industrial as well as academic stakeholders to ensure interoperability among semiconductor companies, and further industrial domains. SC³ implements an industrial reference platform as a de-facto standard (frequently used). This framework acts as a key enabler for realising an agile development - validation - refinement loop of a top-level ontology i.e. Digital Reference (DR). DR comprises a combination of different ontologies of semiconductor supply chains and supply chains containing semiconductors. To that end, the framework will support ontology governance e.g. development, archiving and indexing as well as the validation of high quality and interlinked ontologies and taxonomies. SC³ will incrementally add domain knowledge to the DR; the extended version of DR covers semiconductor domain vocabulary and related sub domains. The platform allows the involvement of all stakeholder groups in a customised fashion and proposes iterative engaging approaches for each community. The DR allows modularly including, developing and extending domain knowledge to provide a connected supply network structure. The project will follow a deliberate piloting methodology in order to deliver the demonstrators needed as proof-of-concept and for evaluation of project’s measurable objectives. SC³ activities will have a strong focus on sustainability and uptake of the project results, this includes on the one hand to keep the established community alive and on the other hand that the semiconductor data documentation, (i.e. the Generic Semiconductor Data Model) will be further developed and maintained even after the project duration.

The BIPER project aims to foster a collaborative partnership in order to develop a blended-learning compatible BIS curriculum based on shared values, eLearning experiences, and sound pedagogical principles. While eLearning has been around for over two decades now, the recent global challenge invoked by the COVID-19 pandemic has put online education into the forefront of academic attention - both as a technological opportunity to maintain the continuity of teaching (at all levels of education) and as a challenge to innovate and apply new methodological approaches. The current pandemic put extra strain and challenge on most universities to retain the quality of their education. It has become clear that innovative approaches are needed - and needed fast: approaches that can help to deliver high-quality education in distance learning format in areas traditionally not well suited for digital training. The challenge concerns not only teaching methods and material but also the teachers and trainers themselves. The academic field of Business Information Systems is a complex area bridging business and organisational topics with questions of applied information technology. Teaching such a multidisciplinary domain which assumes not only knowledge of theoretical concepts and technical skills to use tools but also a problem centred mindset and related problem-solving abilities is a challenge in itself. However, with the heightened need for high-quality online education (offering both distance or blended learning options in the wake of the COVID-19 pandemic) educators of this area face increased difficulties to find appropriate methods and create new content and teaching material. Sharing ideas and experiences regarding what worked and what was less successful could enhance our knowledge of BIS distance education. BIS education in a classroom context may be characterised by what the literature calls 'active learning', which refers to pedagogies that increase and enhance student interaction. This is required by the project-oriented and teamwork-based reality of developing, implementing, and managing IT/IS solutions in an organizational context. Beyond the obvious basics of the trade, interpersonal skills, team building and the ability to combine individual efforts with group work are an essential part of training BIS professionals. While video and audio solutions are usually augmented with less synchronous means such as text messages or sharing files, this still does not make up for lost personal proximity. Using document sharing options and working on the same file together raises new challenges just as much as offering new opportunities. To be successful in this setting of increased complexity and expectations lecturers could use any help they could get - let it be experiences, best practices, successful methodologies, or even ready-made materials.Methodological innovations are needed that can deliver soft skills along with best practices for teaching and learning such skills. This implies digital education that goes beyond the simple demonstration of how to use some software tools but instead could allow the transfer of complex skills and capabilities required by developing and managing modern computer and data systems. Sharing best practices and experiences between institutions of differing cultures is essential in this regard. Furthermore, new methods, methodologies, and techniques need to be explored as well - solutions that could be used both in a fully online setting and could be successful in the context of hybrid and mixed approach educational settings too.The planned project aims at allowing consortiums partners to share their knowledge and expertise concerning the above situation and develop a shared pool of resources benefiting both its members as well as the wider BIS education community.Members of this consortium intend to re-think and re-design BIS curriculum not only under the threats of COVID-19, but on a longer term with the following objectives:•creating a BIS framework in architectural approach in harmony with the accredited learning outcomes and objectives; •increase the granularity of BIS learning units and reallocate them along overall BIS framework;•putting the learning and teaching focus on complex problem-solving and collaborative work;•enhance the interorganisational collaboration in teaching and learning in the online space via identification and sharing best practices;•enhance the use of cloud software infrastructure, develop a framework for the improvement of computer soft skills education at the higher education level;•share (existing) content related to teaching soft computer skills, including but not limited to software development and data analytics;•develop further opportunities for methodological improvement, develop new methods and content (based on those methods) to teach programming and the use of complex analytical techniques and tools.

In rapidly changing health care systems, digitalization, e-health and robotisation are gaining influence. Due to the existing global nurse shortage in Europe, a demand for healthcare and therewith nurses will continue to grow, whilst the supply of available nurses is projected to drop. Therefore, it is expected that the shortages will accelerate in the coming decade and will be more serious than the cyclical shortages of the past. This nursing shortage will ultimately constrain health system reform and innovation, and contribute to escalating costs. ICT, AI and robotization are one way to support health care professionals, enhance interprofessional cooperation and patients` safety. This introduction of ICT, robotisation and other technologies in nursing care will create a disruptive change in the provision of health and nursing care. Furthermore, research shows, that the usage of ICT is still limited within the health care professions and thus in nursing. For that external and internal factors have been identified, e.g. infrastructure not being suitable or the lack of interoperability of different computer and ICT systems, the limited awareness and understanding of ICT concepts. Health care professionals who use ICT complain about the lack of skills and tailored trainings for their needs. Usually nurses have to learn ICT related skills on the job within their working duties. As ICT is rapidly changing and developing towards robotization and AI, the resistance and skepticism towards technology among nursing professionals are expected to grow. The NursingAI project will analyze and forecast the types of skills and competencies needed by health care professionals, especially nurses. By gaining insight of needed competencies and skill, curriculums for trainings and education programs can be enhanced to the actual needs concerning ICT competencies. NursingAI will work towards an assessment and training tool for skills related to AI, robotisation, digitalization and e-health in nursing sectors of Germany, Hungary and the Netherlands. The tool prototype will be tested and evaluated in these countries in order to make them available for local and European VET curriculums and further education programs. These efforts are critical, since 1), nurses should be able to understand and work with novel AI and Information and Communication Technologies (ICT) in order to improve the general quality of care; 2) the current offer of assessment and training methods on AI, robotisation, digitalization and e-health skills in nursing in Europe is very limited, and 3) in order to have a significant amount of AI and robotization skilled nurses in place in 5-10 years time in Europe, investments and changes in the VET curricula need to be initiated now. With the transnationally project, needed competencies in future workplaces will be multiplied and progress made in VET and health care.

"The socio-economic aspect of data and data related industries are crucial for the further development of the European Union and its competitiveness capacities in the global economy. Every day 2.5 quintillion bytes of data are created by different sources while 6.16 million people in Europe worked in data-related jobs in 2016, with a perspective to see the number of workers increasing up to 10.43 million by 2020. On the other side, the overall value of the EU data economy reached almost 300 billion EUR in 2016 and according to the ""high grow"" scenario the value will reach 739 billion by 2020, with an overall impact of 4% in the EU GDP.However, there is an existing gap between total demand and supply of data workers of 420.000 in EU in 2016, with a forecast to face a data skills gap corresponding to 769.000 unfilled positions by 2020. In order to mitigate potential unbalances and to sustain changes in policy making, regulatory framework and educational approach requested by this rapid deployment of new data technologies, EU has shaped its recommendations which underline the importance of reskilling work force developing digital skills for industry and launched its Agendas to boost human capital, employability and competitiveness by modernising education and training curricula/study programs.Facing stated challenges, universities and other HEIs are often lagging behind in their role of developing and offering educational programmes and materials, providing students with skills which market demands, thus indirectly creating a consistent gap between demand and supply of qualified workers. This is even more evident in non-technical sectors where domain-specific data skills are in high demand. The main objective of the ADSEE project is to deliver useful educational and training programme in data science (DS) through: development of educational modules, adaption of contents and methods according to envisaged needs of the target groups, creation of interactive didactic tools and production of guidelines and recommendations on innovative education approaches in DS. Special attention will be paid to data science in non-technical universities and its application in non-technical business, were previous knowledge in this area is not mandatory. The innovativeness of the project lies in the modular approach allowing tailor-made courses development, according to the participants' specific prior knowledge and competences (or in absence of that knowledge/competences) and in a fully functioning online piloting repository which will contribute to the development of participants' new skills and experiences by delivering material in full-scale training case (""from business problem to business usage"") and to fill the gap between increasing demand and limited supply of business sector for practical training methods and approaches. Thanks to a modular approach used to develop educational and training material, all modules will be transferable and applicable in any study program since they will be structured in flexible end-to-end business case avoiding a pure data scientific approach. The partnership comprises 5 partners : Algebra University College Croatia; University of Amsterdam, The Netherlands; German National Library and Leibniz Information Centre for Science and Technology, Germany; Faculty of Information Studies, Slovenia; Arctur ltd, Slovenia.Whereas the project will contribute to the popularisation of Data Science among wider public, the main target groups are higher education institutions and HEIs employees, students, business/industry sector, institutions (ministries of labour, national employment agencies, employers' associations), Digital Innovation Hubs (DIH). ADSEE project addresses individuals with in-depth knowledge about data science, those who are attending technical universities or are working in DS related sectors and individuals who know DS exists, are aware of its potential but still without an expertise to make decisions based on data science. In order to achieve the main objective, project partners have set up a set of activities that will result with five main intellectual outputs. - Report including a repository of existing DS training courses/study programmes and market needs in respect to relevant occupations, with a special attention to the non-technical sectors;- Interactive online repository as a focus point of the full learning materials, a tool for piloting and simulating use-cases in DS;- Transferable educational/training materials/modules covering wide range of different industries and cross-domain topics - At least four piloted and simulated use-cases - Guidelines for DS studies and for a non DS studies (studies that have implemented DS as horizontal element in curricula and studies that haven't implemented DS in curricula at all) including tailoring recommendations in relation to institutions specificities."