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This report aims to support the work of the JRC.B6 (Digital Economy Unit), which provides scientific and technical services to the DG RTD for improving and evolving the GEOSS (Global Earth Observation System of Systems) Platform. In the framework of this Administrative Agreement (called EOVALUE), a specific task deals with the analysis of the GEOSS users and data content. The GEOSS platform is a global hub for Earth Observation (EO) data, representing an overarching infrastructure with the main task of easing discovery and access of data made available by different national and international organizations by means of heterogeneous publication systems. GEOSS is managed and realized under the coordination of the Group on Earth Observations (GEO), an intergovernmental initiative comprising more than 100 national governments and in excess of 100 Participating Organizations aiming to benefit different societal benefit areas by means of Earth Observations. In 2017, an analysis of GEOSS data content and its users was done by JRC.B6. The present work aims to update such an analysis, in a consistent way, and understand the main changes occurred in the last few years., This is the accepted version of EOValue Deliverable 1.1 version 2. The published version is available on the EOValue JRC Science Hub Community. EOValue is a three-year project (2018-20) funded by the H2020 research programme and implemented by the European Commission Joint Research Centre

Digitranscope originated from the JRC Strategy 20301. The strategy identified ten strategic topics on which the JRC should concentrate to anticipate future policy requests. One of these topics was ‘Data and Digital Transformation’, to which the JRC set up two initiatives: the first being a transversal project on ‘Artificial Intelligence and Digital Transformation’, the second being a CAS research project on digital transformation, which was to be more exploratory in nature. The CAS project originally proposed to address two key issues: i) how the information glut triggered by digital transformation reverses the cognitive balance between humans and machines, and ii) the impact of digital information technology on the rules and institutions that guide modern societies. This proposal therefore led to the establishment of two projects in 2017: ‘Human behaviour and machine intelligence’ (HUMAINT)2 and our project, ‘Digital transformation and the governance of human society’ (Digitranscope).

This document presents the contributions discussed at the second institutional workshop on Artificial Intelligence (AI), organized by the Joint Research Centre (JRC) of the European Commission. This workshop was held on 05th July 2019 at the premises of the JRC in Ispra (Italy), with video-conference to all JRC's sites. The workshop aimed to gather JRC specialists on AI and Big Data and share their experience, identify opportunities for meeting EC demands on AI, and explore synergies among the different JRC's working groups on AI. In comparison with the first event, according to the JRC Director General Vladimír Šuchav, the activities and results presented in this second workshop demonstrated a significant development of AI research and applications by JRC in different policy areas. He suggested to think about replicating the event at the premises of diverse policy DGs in order to present and discuss the clear opportunities created by JRC activities. After the opening speech by the JRC Director General Vladimír Šuchav, the research and innovation presentation were anticipated by two presentations by Alessandro Annoni and Stefano Nativi. The first presentation dealt with the results of one year of AI@JRC and six months of fully operational AI&BD community of practice1. The second presentation reported the results of the AI competences survey at JRC. The research and innovation contributions consisted in flash presentations (5 minutes) covering a wide range of areas. This report is structured according to the diverse domain areas addressed by the presenters. While the first part of the workshop was mainly informative, in the second part we collectively discussed about how to move on and evolve the AI&BD community of practice., JRC.B.6-Digital Economy

This document presents a sectoral analysis of AI in health and healthcare for AI Watch, the knowledge service of the European Commission monitoring the development, uptake and impact of Artificial Intelligence for Europe. Its main aim is to act as a benchmark for future editions of the report to be able to assess the changes in uptake and impact of AI in healthcare over time, in line with the mission of AI Watch. The report recognises that we are still at an early stage in the adoption of AI and that AI offers many opportunities in the short term for improved efficiency in administrative and operational processes and in the medium-long term for clinical applications, patients’ care, and increased citizen empowerment. At the same time, AI applications in this sensitive sector raise many ethical and societal issues and shaping the direction of development so that we can maximise the benefits whilst reducing the risks is a key issue. In the global context, Europe is well positioned with a strong research base and excellent health data, which is the pre-requisite for the development of beneficial AI applications. Where Europe is less well placed is in translating research and innovation into industrial applications and in venture capital funding able to support innovative companies to set themselves up and scale up once successful. There are however noticeable exception as the case of the BioNTech that is leading the development of one of the COVID-19 vaccines. It should also be noted that in AI-enabled health start-ups, many of them are in the area of drug discovery, i.e. the domain of BioNTech. Investment in education and training of the healthcare workforce as well as creating environments for multidisciplinary exchange of knowledge between software developers and health practitioners are other key areas. The report recognizes that there are many important policy developments already in the making that will shape future directions, including the European Strategy for Data which is setting up a common dataspace for health, a riskbased regulatory framework for AI to be put in place by the end of 2020, and the forthcoming launch of the Horizon Europe programme as well the Digital Europe Programme with large investments in AI, computing infrastructure, cybersecurity and training. The COVID-19 crisis has also acted as a booster to the adoption of AI in health and the digital transition of business, research, education and public administration. Furthermore, the unprecedented investments of the Recovery Plan agreed in July 2020 may fuel development in digital technologies and health beyond expectation. We are therefore at the junction of a potentially extraordinary period of change which we will be able to measure in future years against the baseline set by this report., JRC.B.6-Digital Economy

The COVID-19 pandemic has created an extraordinary medical, economic and social emergency. To contain the spread of the virus, many countries adopted a lock down policy closing schools and business and keeping people at home for several months. This resulted in a massive surge of activity online for education, business, public administration, research, social interaction. This report considers these recent developments and identifies some early lessons with respect to the present and future development of AI and digital transformation in Europe, focusing in particular on data, as this is an area of significant shifts in attitudes and policy. The report analyses the increasing use of AI in medicine and healthcare, the tensions in data sharing between individual rights and collective wellbeing, the search for technological solutions like contact tracing apps to help monitor the spread of the virus, and the potential concerns they raise. The forced transition to online showed the resilience of the Internet but also the disproportionate impact on already vulnerable groups like the elderly and children. The report concludes that the COVID-19 crisis has acted as a boost for AI adoption and data sharing, and created new opportunities. It has also amplified concerns for democracy and social inequality and showed Europe’s vulnerability on data and platforms, calling for action to address these crucial aspects., JRC.B.6-Digital Economy

An ever-growing number and length of documents, number and depth of topics covered by legislation, and ever new phrases and their slowly changing meaning, these are all contributing factors that make policy analysis more and more complex. As implication, human policy analysts and policy developers face increasing entanglement of both content and semantical levels. To overcome several of these issues, JRC has developed a central pilot tool called AI-KEAPA to support policy analysis and development in any domain. Recent developments in big data, machine learning and especially in natural language processing allow converting unfathomable complexity of many hundreds of thousands of documents into a normalised high-dimensional vector space preserving the knowledge. Unstructured text in document corpora and big data sources, until recently considered just an archive, is quickly becoming core source of analytical information using text mining methods to extract qualitative and quantitative data. Semantic analysis allows us to extract better information for policy analysis from metadata titles and abstracts than from the structured human-entered descriptions. This digital assistant allows document search and extraction over many different sources, discovery of phrase meaning, context and temporal development. It can recommend most relevant documents including their semantic and temporal interdependencies. But most importantly, it helps bursting knowledge bubbles and fast-learning new domains. This way we hope to mainstream artificial intelligence into policy support. The tool is now fit for purpose. It was thoroughly tested in real-life conditions for about two years mainly in the area of legislative impact assessments for policy formulation, and other domains such as large data infrastructure analysis, agri-environmental measures or natural disasters, some of which are detailed in this document. This approach boosts the strategic JRC focus on application of scientific analysis and development. This service adds to the JRC competence and central position in semantic reasoning for policy analysis, active information recommendation, and inferred knowledge in policy design and development., JRC.I.3-Text and Data Mining

This study aims at supporting the policy initiatives to ensure the availability in EC Member States of adequate advanced digital skills in a number of IT domains including Artificial Intelligence, High Performance Computing and Cybersecurity. By making use of the Techno-Economic Segments (TES) analytical approach developed under the PREDICT3 project, the study collects data and builds quantitative indicators to provide a mapping of digital skills in the mentioned technological domains from two complementary perspectives: the existing offer of academic programmes (bachelor, master and doctoral programs), and the demand of profiles by the industry, as reflected by industry activity in the referred fields., JRC.B.6-Digital Economy

This document presents the contributions presented at the first internal workshop on Artificial Intelligence (AI), organized by the Joint Research Centre (JRC) of the European Commission. This workshop was held on 23rd May at the premises of the JRC in Ispra (Italy), with video-conference to all JRC's sites. The workshop aimed to gather JRC specialists on AI to share their experience, to identify opportunities for meeting the EC demands on AI, and explore synergies among different JRC's working groups on AI. The full-day session workshop was organized around three main topical strands entitled Policy support, New Initiatives and Technology Development. Contributions covered a wide range of areas, including applications of AI to Cybersecurity, Transport, Environment, Health and other specific issues. This report is structured according to those main topics of study. According to the JRC Director General Vladimír Šucha: "The workshop was very stimulating and interesting presenting a broad spectrum of activities and competencies across JRC. It gave a great opportunity to build a strong and hopefully useful position in the field of AI/ML". While the first part of the workshop was mainly informative, in the second part we collectively discussed about JRC priorities and the set-up of a Community of Practice (now available at https://webgate.ec.europa.eu/connected/groups/community-of-practice-ai-and-big-data) dealing with AI and Big Data. Finally, the preliminary results of the online survey were presented. All colleagues were excellent in communicating their scientific activity in a flash and efficient way., JRC.B.6-Digital Economy

The Modelling Inventory and Knowledge Management System of the European Commission (MIDAS) is a Commission-wide knowledge management tool for modelling, enabling enhanced transparency and traceability of models in use for EC policy making. It forms an integral part of the Competence Centre on Modelling (CC-MOD) of the Joint Research Centre of the European Commission (JRC). This document describes MIDAS, by providing a bird's-eye view of the MIDAS content, architecture, and functionality, and identifying the benefits of the system for the organisation and in the context of the Better Regulation Agenda., JRC.I.2-Foresight, Modelling, Behavioural Insights & Design for Policy

The INSPIRE geoportal provides the means to search for spatial data sets and spatial data services, and subject to access restrictions, to view and download spatial data sets from the EU Member States within the framework of the INSPIRE Directive. Member States have to provide access to their infrastructures through the INSPIRE geoportal. This provision is a legal obligation. However, many time arises the question what is the benefit or who is really using INSPIRE geoportal and for what purpose? Does it only serve European Commission to monitor INSPIRE implementation in Member States or it has broader usage? This paper provides an overview of INSPIRE Geoportal users based on geoportal usage statistics. We will provide answers on who is searching, what, where they are coming from, etc. To truly understand what INSPIRE-borne statistics tells us, we also need to incorporate other sources as well. We would like to show also how metadata, logs and reports provide interesting insights when enriched by data from EUROSTAT, other infrastructures or social networks.

Impact assessments (IA) are an important tool for better regulation and thus one of the cornerstones of policy making in the European Union. IAs require a benchmark against which the policy options can be compared. This benchmark is usually referred to as baseline or baseline scenario. To the extent possible, baselines in different IAs should be consistent, i.e. the assumptions underlying the baselines should avoid logical and factual contradictions. This report examines IAs from 2011 onwards with a view to check whether baseline assumptions are consistent. The baseline assumptions have been identified using text mining techniques. The focus is on model-based IAs considering that quantitative assumptions are expected to be found predominantly in IAs that make use of models. The findings suggest that, within policy areas, there is a greater degree of consistency than across policy areas. Moreover, baselines assumptions vary more in the course of time than within one year. At the same time, there is still room for improvement as regards the documentation of baseline assumption., JRC.I.1-Modelling, Indicators and Impact Evaluation