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This paper is the first of a series that describes some of the main dataset resources presently shared through the GEOSS Platform. The GEOSS Platform has been created to provide the technological tool to implement the Global Earth Observation System of Systems (GEOSS); it is a brokering infrastructure that presently brokers more than 190 autonomous data catalogs and information systems. The paper analyses the China Satellite datasets and describes the data publishing process from China GEOSS Data Provider to the GEOSS Platform considering both administrative registration as well as the technical registration. The China Satellite datasets are considered as one of the most important satellite data shared by the GEOSS Platform. The analysis provides some insights as well about GEOSS user searches for China Satellite datasets.

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

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

Proposal to adopt SeaDataNet CSR XML encoding as the reference XML implementation of SeaDataNet CSR metadata model. The SeaDataNet infrastructure, its standards, services and products started to build since the mid-1990s under the EU MAST Programmes with the precursor EDMED, EURONODIM, MEDATLAS projects and continued with the EU-FP5 SeaSearch project (2002-2005). Under EU-FP6 Programme, the distributed SeaDataNet system was set up (2006-2011) and continued into its second phase under the EU-FP7 SeaDataNet II project (2011-2015). In the EU HORIZON 2020 SeaDataCloud project, the infrastructure is being upgraded and expanded making use of cloud services, High Performance Computing technology and taking into account the European Open Science Cloud (EOSC) challenge. SeaDataNet CSR XML encoding has been drafted, published and firstly implemented in the context of SeaDataNet, the leading infrastructure in Europe for marine & ocean data management. Its wide implementation, both by data centres within SeaDataNet and by external organizations makes it also a de-facto standard in the Europe region. The acknowledgement of SeaDataNet CSR XML encoding as a recommended standard by IODE/JCOMM will further favour interoperability between European data centres and outreach to the broader marine community. Published Refereed Current 14.a N/A Multi-organisational Method Specification of criteria Reports with methodological relevance

Report on the first proposal of EVs for selected themes. It will include description and justification of inclusion. It will collect drafts of SBA-specific EVs for Carbon (CMCC), Health and Pollution (CNR-IIA), Ecosystems (CNRISAC), Biodiversity (CNR- ISSIA), Energy (ARMINES), Disasters (TIWAH) and Oceans (CSIC). It will also include a report on the Co-located Essential Variables Workshop on M7.

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

Destination Earth (DestinE) is an initiative initiated and coordinated by the European Commission’s Directorate-General for Communications Networks, Content and Technology (DG CNECT) in support of the European Green Deal1 and as contribution to the establishment of the Green Deal Data Space, one of several data spaces envisaged in the European Strategy for Data (COM2020 66 final). The overall objective of DestinE is to develop a service infrastructure that: - serves specific EU needs based on clearly identified EU policy priorities and user needs in relation to e.g. the Green Deal, and - is at the same time firmly based on European values, such as commitment to quality and transparency in order to build trust in evidence-based policy-making among all stakeholders. DestinE will include a shared horizontal layer including computer processing, data, software, and infrastructure and some vertical applications, Digital Twins (DTs), in selected thematic areas responding to priority policy use cases. To identify these priorities, the Joint Research Centre of the European Commission (JRC) has been tasked by DG CNECT to collect a number of potential use cases for DestinE representing needs of policy DGs in the Commission. This document presents 30 use cases received from six policy DGs, the JRC and 5 relevant European stakeholders. The use cases were preliminarily evaluated and clustered according to their assumed maturity level in terms of policy, scientific and anticipatory potential. Following a series of interactions with all stakeholders consulted, JRC identified two initial DTs on: - Extreme Earth issues (disaster risk management in relation to extreme weather-induced natural disasters); - Climate change adaptation issues (primarily food and water supply security). Another DT on digital oceans (around food and energy issues) was introduced as a suggestion to DG CNECT to be possibly developed in the second phase of DestinE’s implementation. Although this report is certainly neither exhaustive nor fully descriptive e.g. in relation to the assumed maturity levels of the mentioned use cases, it served nevertheless as a useful input to DG CNECT’s final definition of the scope of DTs whose development would be prioritized in the course of the DestinE implementation., JRC.B.6-Digital Economy

Digital Twins have been around for decades, especially in industrial processes. However, with the recent advent of transformative digital technologies (i.e. IoT, AI, ML, Big Data analytics, and ubiquitous connectivity) Digital Twins are changing most of the society sectors, providing the most advance pattern to make the physical and the digital worlds interact. Naturally, this is also true for the scientific sector, and in particular those disciplines that are engaged in understanding and addressing the Global Change effects. Thanks to the Digital Twins growing development, for the first time, it is possible to envision a digital replica of important natural and social phenomena and processes, trying to anticipate their behaviour. There exist diverse definitions of Digital Twins, reflecting the diverse concerns of the industrial, scientific, and standardization sectors (in particular IEEE and ISO/IEC), which have been working on their description and realization. The main interaction features characterizing a Digital Twin are: - Interoperability; - Information Model; - Data Exchange; - Administration; - Synchronization; - Push mode (Publish Subscribe). According the scientific research, there is still the need to address the following challenges to push Digital Twins implementation and effective use: - Unify data and model standards; - Share data and models; - Innovate on services; - Establish forums. In industry, Digital Twins are well used in “vertical” sectors/application areas, including: manufacturing, energy, smart cities, farming, building, healthcare. For the applied scientific and research areas, this preliminary study recognized several areas., JRC.B.6-Digital Economy

This JRC report aims to investigate the maturity level of Internet of Things (IoT) on-going development and reflect upon its contribution to the Digital Transformation of our Society. Besides, the document tries to identify possible challenges and opportunities by analysing some global data sources. In doing that, we also assessed the advantages and limitations of using multiple different data sources. The analyses results can be used as a good starting point for a further and more systematic socio-economic analysis. This document is a result of a more general work of JRC.B6 that developed a methodological approach for the identification of emerging technological trends to be applied universally in ifferent technological domains., JRC.B.6-Digital Economy

The Report ‘Cybersecurity – Our Digital Anchor’ brings together research from different disciplinary fields of the Joint Research Centre (JRC), the European Commission's science and knowledge service. It provides multidimensional insights into the growth of cybersecurity over the last 40 years, identifying weaknesses in the current digital evolution and their impacts on European citizens and industry. The report also sets out the elements that potentially could be used to shape a brighter and more secure future for Europe’s digital society, taking into account the new cybersecurity challenges triggered by the COVID-19 crisis. According to some projections, cybercrime will cost the world EUR 5.5 trillion by the end of 2020, up from EUR 2.7 trillion in 2015, due in part to the exploitation of the COVID-19 pandemic by cyber criminals. This figure represents the largest transfer of economic wealth in history, more profitable than the global trade in all major illegal drugs combined, putting at risk incentives for innovation and investment. Furthermore, cyber threats have moved beyond cybercrime and have become a matter of national security. The report addresses relevant issues, including: - Critical infrastructures: today, digital technologies are at the heart of all our critical infrastructures. Hence, their cybersecurity is already – and will become increasingly – a matter of critical infrastructure protection (see the cases of Estonia and Ukraine). - Magnitude of impact: the number of citizens, organisations and businesses impacted simultaneously by a single attack can be huge. - Complexity and duration of attacks: attacks are becoming more and more complex, demonstrating attackers’ enhanced planning capabilities. Moreover, attacks are often only detected post-mortem . - Computational power: the spread of malware also able to infect mobile and Internet of Things (IoT) devices (as in the case of Mirai botnet), hugely increases the distributed computational power of the attacks (especially in the case of denial of services (DoS)). The same phenomenon makes the eradication of an attack much more difficult. - Societal aspects: cyber threats can have a potentially massive impact on society, up to the point of undermining the trust citizens have in digital services. As such services are intertwined with our daily life, any successful cybersecurity strategy must take into consideration the human and, more generally, societal aspects. This report shows how the evolution of cybersecurity has always been determined by a type of cause-and-effect trend: the rise in new digital technologies followed by the discovery of new vulnerabilities, for which new cybersecurity measures must be identified. However, the magnitude and impacts of today's cyber attacks are now so critical that the digital society must prepare itself before attacks happen. Cybersecurity resilience along with measures to deter attacks and new ways to avoid software vulnerabilities should be enhanced, developed and supported. The ‘leitmotiv’ of this report is the need for a paradigm shift in the way cybersecurity is designed and deployed, to make it more proactive and better linked to societal needs. Given that data flows and information are the lifeblood of today’s digital society, cybersecurity is essential for ensuring that digital services work safely and securely while simultaneously guaranteeing citizens’ privacy and data protection. Thus, cybersecurity is evolving from a technological ‘option’ to a societal must. From big data to hyperconnectivity, from edge computing to the IoT, to artificial intelligence (AI), quantum computing and blockchain technologies, the ‘nitty-gritty’ details of cybersecurity implementation will always remain field-specific due to specific sectoral constraints. This brings with it inherent risks of a digital society with heterogeneous and inconsistent levels of security. To counteract this, we argue for a coherent, cross-sectoral and cross-societal cybersecurity strategy which can be implemented across all layers of European society. This strategy should cover not only the technological aspects but also the societal dimensions of ‘behaving in a cyber-secure way’. Consequently, the report concludes by presenting a series of possible actions instrumental to building a European digital society secure by design., JRC.E.3-Cyber and Digital Citizens' Security

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

The rationale of this document is to create a formal documentation of the Brokering architecture, proven successful in ODIP prototype 1+, as well as in several other real-world and prototype use cases, to serve as a best practice. Wider recognition and interest in the functionalities of this middleware (which is transparent by its nature) are expected as an outcome of this publication. ODIP Prototype 1+ (in the context of the Ocean Data Interoperability Platform Coordination and Support Action of the EU Research Infrastructures programme) aims at implementing interoperability between the following autonomous and distributed systems: SeaDataNet CDI, US NODC, and IMOS MCP. The prototype demonstrates data discovery and access services using a brokering middleware that is utilized by a couple of Web-portals:the global IODE-ODP and GEOSS portal. Published The spatial scope is not indicated, being ODIP broker scope global. SDG, EOV, instruments and parameters are not indicated as well, because the ODIP broker pose no constraint on particular values of these elements, supporting in principle all of them, depending on the actual brokered sources. With the currently brokered sources in ODIP the space of parameters is well covered. Current TRL 6 System/subsystem model or prototyping demonstration in a relevant end-to-end environment (ground or space) Best Practice

Definition of SeaDataNet metadata profile, according to ISO 19115 international standard specification, Version 11.0.0, January 2019. This document has been drafted in the context of the EU FP7 SeaDataNet project and EU H2020 SeaDataCloud project by CNR. “ISO/IEC Directives, Part 2: Rules for the structure and drafting of International Standards”was used as a reference for the drafting. Published Current Best Practice Guide

Definition of SeaDataNet CSR metadata profile, according to ISO 19115 international standard specification, Version 4.0.0, January 2019. This document has been drafted in the context of the EU FP7 SeaDataNet II project and EU H2020 SeaDataCloud project by CNR. “ISO/IEC Directives, Part 2: Rules for the structure and drafting of International Standards” was used as a reference for the drafting. Published Current Best Practice Guide

Encoding of the SeaDataNet metadata profile in XML, by means of both XML schema and Schematron rules definitions. This document has been drafted in the context of the EU FP7 SeaDataNet II project and EU H2020 SeaDataCloud project by CNR. “ISO/IEC Directives, Part 2: Rules for the structure and drafting of International Standards”was used as a reference for the drafting. Published Current Best Practice Guide

International audience; Der paneuropäische Virtual Hub (pEVH), der im Rahmen des europäischen Projekts ENERGIC-OD entwickelt wurde, ver-einfacht die Nutzung von offenen Geodaten für alle Nutzer und insbesondere für KMUs. Er ist ein zentraler Zugangs-knoten zu einer Vielzahl von Datensätzen. Er verbindet gro-ße Open-Data-Plattformen und bietet darüber hinaus Mehr-werte wie etwa die semantische Erkennung für mehrspra-chige Metadaten und eine Datenformat-Harmonisierung. Die pEVH-Dienste sind über ein von der ESA entwickeltes Geo-portal sowie über Standarddienste und für Entwickler über dedizierte APIs zugänglich. Die grundlegenden Funktionen des pEVH werden allen Benutzern kostenlos zur Verfügung ste-hen, wohingegen einige Premium-Funktionen für eine geringe Gebühr zugänglich sind. Der pEVH wird mindestens bis zum Ende des Jahres 2020 betrieben und soll die Lücke bei nach-haltigen Geschäftsmodellen rund um Open Data schließen und forschungsgetriebene Projektergebnisse auf den Markt bringen.; The pan-European Virtual Hub (pEVH), developed as part of the ENERGIC-OD European project, facilitates the usage of geospatial information open data to all users, and SMEs in particular. It is a single point of access to a wide range of datasets. It brokers major open data platforms, and provides added-value services including semantic discovery for multilingual metadata, and data format harmonization. The pEVH services are accessible through a geoportal developed by ESA and through standard services and dedicated APIs for developers. Basic functions of the pEVH will be available for free to all users, with some premium features accessible for a low charge (thus embracing the freemium revenue model). The pEVH will function until at least the end of year 2020, and it bridges the gap between a sustainable business model around open data commercialization, as well as bringing research driven project outputs to the market

We are only at the beginning of a rapid period of transformation of our economy and society due to the convergence of many digital technologies. Artificial Intelligence (AI) is central to this change and offers major opportunities to improve our lives. The recent developments in AI are the result of increased processing power, improvements in algorithms and the exponential growth in the volume and variety of digital data. Many applications of AI have started entering into our every-day lives, from machine translations, to image recognition, and music generation, and are increasingly deployed in industry, government, and commerce. Connected and autonomous vehicles, and AI-supported medical diagnostics are areas of application that will soon be commonplace. There is strong global competition on AI among the US, China, and Europe. The US leads for now but China is catching up fast and aims to lead by 2030. For the EU, it is not so much a question of winning or losing a race but of finding the way of embracing the opportunities offered by AI in a way that is human-centred, ethical, secure, and true to our core values. The EU Member States and the European Commission are developing coordinated national and European strategies, recognising that only together we can succeed. We can build on our areas of strength including excellent research, leadership in some industrial sectors like automotive and robotics, a solid legal and regulatory framework, and very rich cultural diversity also at regional and sub-regional levels. It is generally recognised that AI can flourish only if supported by a robust computing infrastructure and good quality data: • With respect to computing, we identified a window of opportunity for Europe to invest in the emerging new paradigm of computing distributed towards the edges of the network, in addition to centralised facilities. This will support also the future deployment of 5G and the Internet of Things. • With respect to data, we argue in favour of learning from successful Internet companies, opening access to data and developing interactivity with the users rather than just broadcasting data. In this way, we can develop ecosystems of public administrations, firms, and civil society enriching the data to make it fit for AI applications responding to European needs. We should embrace the opportunities afforded by AI but not uncritically. The black box characteristics of most leading AI techniques make them opaque even to specialists. AI systems are currently limited to narrow and well-defined tasks, and their technologies inherit imperfections from their human creators, such as the well-recognised bias effect present in data. We should challenge the shortcomings of AI and work towards strong evaluation strategies, transparent and reliable systems, and good human-AI interactions. Ethical and secure-by-design algorithms are crucial to build trust in this disruptive technology, but we also need a broader engagement of civil society on the values to be embedded in AI and the directions for future development. This social engagement should be part of the effort to strengthen our resilience at all levels from local, to national and European, across institutions, industry and civil society. Developing local ecosystems of skills, computing, data, and applications can foster the engagement of local communities, respond to their needs, harness local creativity and knowledge, and build a human-centred, diverse, and socially driven AI. We still know very little about how AI will impact the way we think, make decisions, relate to each other, and how it will affect our jobs. This uncertainty can be a source of concern but is also a sign of opportunity. The future is not yet written. We can shape it based on our collective vision of what future we would like to have. But we need to act together and act fast., JRC.B.6-Digital Economy

Scuola in Scienza e Tecnica "Bernardino Telesio", Ciclo XXVI, a.a. 2015-2016 University of Calabria

The ECOPOTENTIAL project, funded under the Horizon 2020 Research and Innovation programme aims at building a unified framework for ecosystem studies and management of protected areas. To achieve such objective, open and interoperable access to data and knowledge is assured by the GEO Ecosystem Virtual Laboratory Platform (ECOPOTENTIAL VLab). The concept of ECOPOTENTIAL VLab stems from the need of moving from open data to open science as a new vision of participatory scientific research. Therefore, it aims not only to data sharing but more generally to support the ecosystem community-of-practice in research activities for informed decision-making in ecosystem management. The ECOPOTENTIAL VLab provides multiple entry points to access information at different semantic level depending on the user's specific interest, ranging from ecosystems, protected areas, storylines (e.g. user scenarios for protected areas study and management), workflows (e.g. business processes necessary for storylines), algorithms (e.g. models and procedures necessary for implementing workflows) and data. All the information artifacts have an open representation and are linked together according to a general ECOPOTENTIAL ontology, allowing users'navigation among different concepts. In particular, users have access to in-situ data from selected campaigns, and from European and global observation networks and programmes, like LTER DEIMS, OBIS, GBIF, LIFEWATCH. They have also access to raw and pre-processed remote-sensing data including Sentinel 1/2 and Landsat. Users have also access to workflows represented as BPMN diagrams, and through the ECOPOTENTIAL VLab they can run workflows selecting input data, to generate essential variables, indicators and indices. Users can share algorithm as code through GitHub, or processing services as OGC WPS and integrate them in new workflows. The architecture of the GEO Ecosystem Virtual Laboratory is based on a set of principles currently shared in the scientific research communities, with particular reference to the GEO initiative, including GEOSS Data Sharing Principles, GEOSS Data Management Principles and GEOSS Architecture Principles. Moreover, since ECOPOTENTIAL participates in the Horizon 2020 pilot action on open access to research data, the activities of the ECOPOTENTIAL Consortium for the definition of the ECOPOTENTIAL Data Management Plan are a fundamental input for the architecture of the ECOPOTENTIAL VLab. The design of the ECOPOTENTIAL Virtual Laboratory puts its basis on past experiences in building System of Systems through a brokering approach. The mature data brokering approach will be complemented with innovative semantic technologies - including concept-based queries and annotations - and support of discovery and invocation of workflows implementing storylines on multiple protected areas contributing to enable the open science vision in ecosystem science.

In November 2016, the Paris Agreement entered into force calling Parties to strengthen their cooperation for enhancing adaptation and narrowing the gap between climate science and policy. Moreover, climate change has been identified as a central challenge for sustainable development by the United Nations 2030 Agenda for Sustainable Development. Data provide the basis for a reliable scientific understanding and knowledge as well as the foundation for services that are required to take informed decisions. In consequence, there is an increasing need for translating the massive amount of climate data and information that already exists into customized tools, products and services to monitor the range of climate change impacts and their evolution. It is crucial that these data and information should be made available not in the way that they are collected, but in the way that they are being used by the largest audience possible. Considering that climate data is part of the broader Earth observation and geospatial data domain, the aim of this paper is to review the state-of-the-art geospatial technologies that can support the delivery of efficient and effective climate services, and enhancing the value chain of climate data in support of the objectives of the Global Framework for Climate Services. The major benefit of spatially-enabling climate services is that it brings interoperability along the entire climate data value chain. It facilitates storing, visualizing, accessing, processing/analyzing, and integrating climate data and information and enables users to create value-added products and services.

In October 2014, the ENERGIC-OD (European NEtwork for Redistributing Geospatial Information to user Communities - Open Data) project, funded by the European Union under the Competitiveness and Innovation framework Programme (CIP), has started. The objective of the project is to facilitate the use of open (freely available) geographic data from different sources for the creation of innovative applications and services through the creation of Virtual Hubs. Data and data services heterogeneity is recognized as one of the major barriers to open data reuse. It imposes end-users and developers to spend a lot of effort in accessing different infrastructures and harmonize datasets. Such heterogeneity cannot be completely removed through the adoption of standard specifications for service interfaces, metadata and data models, especially in interdisciplinary contexts. ENERGIC-OD Virtual Hubs address heterogeneity adopting a mediation and brokering approach: specific components (brokers)are dedicated to harmonize service interfaces, metadata and data models, enabling seamless discovery and access to heterogeneous infrastructures and datasets. ENERGIC OD will deploy a set of five Virtual Hubs at national level in France, Germany, Italy, Poland, Spain and an additional one at the European level. ENERGIC-OD Consortium will develop an initial set of ten different multidisciplinary applications on top of the deployed VHs. The main expected impact of VHs is the creation of new business opportunities opening up access to Research Data and Public Sector Information.

The ConnectinGEO Observation Inventory (OI) is created and populated using the current information in the metadata concentrated in the GEO Discovery and Access Broker (DAB) of the GEOSS Common Infrastructure (GCI) to analyse the observations and measurements currently available in it. WP4 defined a high-level process for the population of the Observation Inventory: (i) retrieve the full metadata content for each record in the GEO DAB, (ii) extract/Infer extra semantics (connecting to external knowledge systems when needed), and (iii) generate enriched metadata and write it to the OI. The OI system architecture was designed and developed. The first version of the OI was created and populated using the current information in the metadata concentrated in the GEO DAB. The first population process was run in December 2015, resulting in a total of more than 1.6M harvested metadata records. The developed OI is accessible online and can be used as a data source by different analysis tools, which create plots, report, or summary statistics useful for the ConnectinGEO gap analysis. A simple Web Client was developed to demonstrate how to interrogate the OI and provide also basic examples of how the developed OI can be used by web-based analysis tools.