The last two decades, if one looks backward, the politics, economies and the society overall are challenged from the speed and scale of the digitalisation. Speed in the sense of emerging opportunities that economies and societies have to adapt to and be ready to explore, in the sense of exponentially growing need to adapt our knowledge and skills, and last but not least overcoming and removing legal and cultural barriers hindering the full use of data’s potential based on fair and security principles. In the same time citizens are overwhelmed from their totally different expectations about the future of our world because of these rapid digital processes and are often left alone to understand or adapt to what is known or accessible. The EC and the EP moved forward many important policies in the direction of holistic and more transparent approach to those changes, including the latest Open Data Directive. Of course, this considerable change and preparatory actions couldn’t be sustainable without taking important steps in reforming and modernising our research and innovation ecosystems. In this respect the Council of the EU adopted a number of important recommendations, some of which are in the Conclusions of 27 May 2016 on "The transition towards an Open Science system" and Council conclusions on "Accelerating knowledge circulation in the EU" from 29 of May 2018 and Shaping Europe's Digital Future - Council Conclusions (9 June 2020). Still, the biggest question is what exactly is the scale of the digitalisation and what should be the scale in the sense of use and reuse of data so that those changes to go in a harmonised way and approach with the capacity of all of us to assimilate and understand what cultural, practical and social impact will big data and AI have. I believe that the best answers one could find and explore and then test and exploit is the research and innovation sector where we already have at least one more ingredient to support us all in meeting all the challenges and it is called - risk. Debating on EU level how much resilient and prepared are our national systems to adopt open science and FAIR data principles, we all unite around the necessity to support and stimulate modern research infrastructure, networks, collaborative projects as well as stimulus for career development including acquiring particular skills. At the same time, one notices the differences in the preparedness of universities and research organisation towards this major socio-economic transformation because of lack of cross-institutional cooperation and understanding of the importance of use and reuse research data as evidence for smart policies, and second because of delayed realisation of open market and free flow of data throughout the EU, based on high quality standards.

Karina Angelieva Deputy Minister of Education and Science in Bulgaria

This paper will look at the 8 pillars of Open Science, as defined by the European Commission and described in the LERU (League of European Research Libraries) Open Science Roadmap, and which be analysed in the forthcoming LERU paper on Best Practice in adopting Open Science principles and policies. What are the strengths and challenges in each of the 8 pillars of Open Science and what is the range of responses that universities could make? In this landscape, the paper will then look at four of the 8 pillars, Open Access Publishing, Research Data Management and Open data E-Infrastructures (European Open Science Cloud), Promotions/Rewards and the responsible use of Bibliometrics, and Citizen Science. It will take UCL (University College London) as an exemplar of good practice and demonstrate with real life examples how this university has implemented new platforms and services, established new policies and practice, showing the benefits and the challenges of these approaches.

Paul Ayris UCL (University College London)

We are stepping into an era with unprecedented trends of cross-disciplinary and cross-border collaboration for science and research. A new research paradigm is shaping by applying increasingly machine learning, and by harnessing the most advanced computing facilities and software, to handle those huge data. The advanced infrastructure for this new paradigm and open science is on demand. After decades sustainably developing and operating the cyber-infrastructure of Chinese Academy of Sciences (CAS), we started to design and develop a new converge infrastructure of network, computing and data, which called China Science and Technology Cloud（CSTCloud）. Driven by new technologies in high speed network, cloud computing, big data and machine learning, CSTCloud aims to develop next-generation e-infrastructure for research to serve domestic science discovery and global science collaborations. CSTCloud is a national platform to provide scientists with efficient and integrated cloud solutions in the retrieval, access, use, transaction, delivery and other aspects of sharing information and relevant services. CSTCloud was launched to provide services at the end of 2019, which collected 400 shared science software and Petabyte scale Multidisciplinary open data with its computing capacity and cloud storage reaching over 315 PF and over 150 PB respectively. Priorities include but are not limited to one-stop and tailored services for scientists, advanced demonstrations driven by key research initiatives, open science practices, and multilateral collaboration and interoperability. We will update the new progress of CSTCloud in technique framework, resources, services, and some typical using cases. We will discuss some key challenges of the implementation technique, resource sharing policies and operation mechanics. We will also explore the possibility to make alignment of different national, regional open science platform to be a global open science cloud the world, to deal with complex, large-scale problems.

Li Jianhui Chinese Academy of Science

The Open Data Directive of the European Union of 2019 is an essential upgrade of previous Public Sector Information (PSI) Directives from 2003 and 2013. It is the public sector that has the pioneering role to lay the foundations for a growing data economy. The scope of the new Directive has been extended to public undertakings and to research data with a strong impetus on Open Science. With the Directive, EU Member States have agreed on a common legal framework on the re-use of open data across the continent. The fact that the same rules apply for all EU Member States within the EU Single Market and that these rules are also adopted by partnering countries makes this legal framework a valid benchmark on a global scale. The new concept of high value datasets aims to boost the availability and re-use of selected datasets alongside with improved data quality standards. The European Union is committed to open markets and the free flow of data, based on high European standards. Open data is a cornerstone of emerging European data spaces. The mission is to develop thriving data ecosystems through collaboration, innovation and research as fundamental European policies.

Martin Semberger Austrian Federal Ministry for Digital and Economic Affairs

Panelists: Karina Angelieva, Deputy Minister of Education and Science in Bulgaria Dr. Paul Ayris, University College London Prof. Li Jianhui, Chinese Academy of Science Martin Semberger, Austrian Federal Ministry for Digital and Economic Affairs Dr. Stefan Hanslik, Austrian Federal Ministry of Education, Science and Research Marie Timmermann, Science Europe Chair and Moderator: Dr. Paolo Budroni, TU Wien Co-chair: Dr. Tiberius Ignat, Scientific Knowledge Services

Paolo Budroni TU Wien Bibliothek

Marie Timmermann Science Europe

Dr. Stefan Hanslik Austrian Federal Ministry of Education, Science and Research

Martin Semberger Austrian Federal Ministry for Digital and Economic Affairs

Li Jianhui Chinese Academy of Science

Karina Angelieva Deputy Minister of Education and Science in Bulgaria

Paul Ayris UCL (University College London)

Closing Notes

Mag. Beate Guba MSc Library Director TU Wien