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The National Research Council of Italy (CNR) is involved in the E-Cabin project, which aims to create a futuristic and intelligent cabin in order both to improve the well- being and satisfaction of passengers and to minimize the on-board waste by using advanced consumption control.

TRAME is a research infrastructure for medieval manuscripts. The TRAME engine scans a set of sources for searched terms and retrieves links to a wide range of possible information, from simple reference, to detailed manuscript record, to full text transcriptions. Currently, it is possible to perform queries by: free-text, shelfmark, author, title, date, copyst or incipit, on more than 80 selected scholarly digital resources across EU and USA. Since 2014 September 1st, TRAME has entered a new phase and the current work is focused on: extending the meta-search approach to other web resources, leveraging the users interaction to define an ontology for medieval manuscripts, re-designing the front-end towards a new UX approach.

Despite the hype, the effective implementation of Open Science is hindered by several cultural and technical barriers. Researchers embraced digital science, use “digital laboratories” (e.g. research infrastructures, thematic services) to conduct their research and publish research data, but practices and tools are still far from achieving the expectations of transparency and reproducibility of Open Science. The places where science is performed and the places where science is published are still regarded as different realms. Publishing is still a post-experimental, tedious, manual process, too often limited to articles, in some contexts semantically linked to datasets, rarely to software, generally disregarding digital representations of experiments. In this work we present the OpenAIRE Research Community Dashboard (RCD), designed to overcome some of these barriers for a given research community, minimizing the technical efforts and without renouncing any of the community services or practices. The RCD flanks digital laboratories of research communities with scholarly communication tools for discovering and publishing interlinked scientific products such as literature, datasets, and software. The benefits of the RCD are show-cased by means of two real-case scenarios: the European Marine Science community and the European Plate Observing System (EPOS) research infrastructure. This work is partly funded by the OpenAIRE-Advance H2020 project (grant number: 777541; call: H2020-EINFRA-2017) and the OpenAIREConnect H2020 project (grant number: 731011; call: H2020-EINFRA-2016-1). Moreover, we would like to thank our colleagues Michele Manunta, Francesco Casu, and Claudio De Luca (Institute for the Electromagnetic Sensing of the Environment, CNR, Italy) for their work on the EPOS infrastructure RCD; and Stephane Pesant (University of Bremen, Germany) his work on the European Marine Science RCD. First Online 30 August 2019

In the framework of the H2020 INDIGO-DataCloud project, we have implemented an advanced solution for the automatic deployment of digital data repositories based on Invenio, the digital library framework developed by CERN. Exploiting cutting-edge technologies, such as Docker and Apache Mesos, and standard specifications to describe application architectures such as TOSCA, we are able to provide a service that simplifies the process of creating and managing repositories of various digital assets using cloud resources. An Invenio-based repository consists of a set of services (e.g. database, message queue, cache, workers and frontend) that need to be properly installed, configured and linked together. These operations, along with the provisioning of the resources and their monitoring and maintenance, can be challenging for individual researchers or small-to-moderate-sized research groups. To this purpose, the INDIGO-DataCloud platform provides advanced features for orchestrating the deployment of complex virtual infrastructures on distributed cloud environments: it is able to provision the required resources automatically over heterogeneous and/or hybrid cloud infrastructures and to configure them automatically ensuring dynamic elasticity and resilience. This approach has been successfully adapted to support the needs of the researchers and scholars in the domain of the Digital Arts and Humanities.

The rapid development of new digital tools and infrastructures in the last years, and their application to a variety of disciplines has transformed how we store, access and retrieve information. This has also shaped the ways knowledge is presented and reused in diverse cultural contexts. The exploreAT! project builds upon not only Austrian, but also European cultural identity from the aspect of language, in particular dialects. Unlike standard languages, dialects are in times of globalization under considerable threat of diminishing, and this ultimately poses a risk to the intangible record that is language and through which a history of tangible culture is expressed. In this paper we elaborate on the possibilities digital means and the infrastructure and services of the EGI-Engage project in revealing and giving access to unique traditional cultural knowledge contained in a non-standard language resource on the example of the Bavarian dialects in Austria (DBÖ). Digital tools and services allow our heterogeneous corpus of data to be virtually exploited and preserved. The flexibility of the internet allows these data to become not only visible, but searchable and extractable. Through digitization efforts, and the use of European infrastructures the hidden cultural narratives within the data can be uncovered, enriched and shared for the benefit of information and knowledge society.

In 2018, the European Strategic Forum for research infrastructures (ESFRI) was tasked by the Competitiveness Council, a configuration of the Council of the EU, to develop a common approach for monitoring of Research Infrastructures' performance. To this end, ESFRI established a working group, which has proposed 21 Key Performance Indicators (KPIs) to monitor the progress of the Research Infrastructures (RIs) addressed towards their objectives. The RIs were then asked to assess their relevance for their institution. The paper aims to identify the relevance of certain indicators for particular groups of RIs by using cluster and discriminant analysis. This could contribute to development of a monitoring system, tailored to particular RIs. To obtain a typology of the RIs, we first performed cluster analysis of the RIs according to their properties, which revealed clusters of RIs with similar characteristics, based on to the domain of operation, such as food, environment or engineering. Then, discriminant analysis was used to study how the relevance of the KPIs differs among the obtained clusters. This analysis revealed that the percentage of RIs correctly classified into five clusters, using the KPIs, is 80%. Such a high percentage indicates that there are significant differences in the relevance of certain indicators, depending on the ESFRI domain of the RI. The indicators therefore need to be adapted to the type of infrastructure. It is therefore proposed that the Strategic Working Groups of ESFRI addressing specific domains should be involved in the tailored development of the monitoring of pan-European RIs. Comment: 15 pages, 8 tables, 3 figures

This document is Deliverable 6.1, "Impact Assessment document", elaborated in the context of E-RIHS PP, WP-06, Task 6.4. The two analysis of this task have been outsourced and, following a public tender, the procurer organization is Centre for Industrial Studies (CSIL), located in Milano, Italy.

In the framework of the H2020 INDIGO-DataCloud project, we have implemented an advanced solution for the automatic deployment of digital data repositories based on Invenio, the digital library framework developed by CERN. Exploiting cutting-edge technologies, such as Docker and Apache Mesos, and standard specifications to describe application architectures such as TOSCA, we are able to provide a service that simplifies the process of creating and managing repositories of various digital assets using cloud resources. An Invenio-based repository consists of a set of services (e.g. database, message queue, cache, workers and frontend) that need to be properly installed, configured and linked together. These operations, along with the provisioning of the resources and their monitoring and maintenance, can be challenging for individual researchers or small-to-moderate-sized research groups. To this purpose, the INDIGO-DataCloud platform provides advanced features for orchestrating the deployment of complex virtual infrastructures on distributed cloud environments: it is able to provision the required resources automatically over heterogeneous and/or hybrid cloud infrastructures and to configure them automatically ensuring dynamic elasticity and resilience. This approach has been successfully adapted to support the needs of the researchers and scholars in the domain of the Digital Arts and Humanities.

One of the main goals of the PARTHENOS project (Pooling Activities, Resources and Tools for Heritage E-research Networking, Optimization and Synergies - EC-H2020-RIA grant agreement 654119) is to bridge existing DHIs by forming a federation where researchers of different sectors of the Humanities can collaborate, share data, services and tools in an integrated environment. PARTHENOS will produce a complete technical framework for the federation, enabling transparent access to resources managed by different DHIs and enabling the creation and operation of Virtual Research Environments where researchers with different backgrounds can collaborate on specific research topics.

This current PhD thesis aims at researching solutions to the long-standing gap in the research infrastructure field of formal modelling and discovery of information. Research Infrastructures (RIs) are facilities, resources and services used by the research community to conduct research and promote innovation. They provide access to tools, data and algorithms, pooled on working environments named Virtual Research Environments (VREs). Due to their nature, Research Infrastructures (RIs) are a heterogeneous landscape of resource types and diverse, often redundant, models for describing the same resource entities. Such diversity drastically diminishes the capabilities of a consistent fruition of the knowledge and skills available within an infrastructure, and ultimately limits the creation of federations of RI. The current state of knowledge in the field is even more complex due to the emerging concept of Hybrid Data Infrastructures (HDIs), which combine on-premises resources with resources provisioned by cloud and/or grid computing infrastructures. The focus of this study is to address the critical aspects of this heterogeneity and provides to the research infrastructure field both the conceptual and analytical instruments for expanding the scale at which the infrastructures currently operate. The following research questions are investigated in this study: - Research question 1: Is it possible to formalise a uniform resource model to seamlessly federate research infrastructures? - Research question 2: To what extent do state-of-the-art discovery algorithms need to be amended to properly handle VREs across Hybrid Data Infrastructures? - Research question 3: To what extent does the interface of a discovery service can support the new model and algorithms? First objective is attained with the definition of a resource model open by design. An accurate mathematical notation presents a minimal but powerful model consisting of few constructs. This is an abstract model, which can be instantiated to accommodate almost every possible scenario. Second objective is confronted with the design of a novel communication model based on the concept of transaction. Transactional models are not a new idea; rather they have been extensively described in the literature since the 80s. However, this work identifies a misapplication of these models in the context of research infrastructure and proposes changes to support the emerging requirements in the field. Lastly, the third objective refers to the impact that the first two questions have on architectural aspects of the services devoted to distribute the information in a research infrastructure. This point is deeply investigated with a detailed design of a production-ready solution to prove the validity and accuracy of the theoretical aspects of this thesis. The originality of the proposed thesis consists also in its methodology. In fact, this dissertation offers an innovative analytical and methodological approach to address these research questions. A key-enabling component of modern Hybrid Data Infrastructures, the Information System (IS), is used as platform to validate this work. An IS is central to all the themes tackled in this thesis. It exploits the resource model, plays the role of registry inside the infrastructure, deals with an intensive communication with all the other actors and works with the heterogeneity of such a context. Its ultimate goal is to provide uniform views of the resources assigned to each VRE, regardless of their origin. The study presented in this thesis has been conducted within the InfraScience group, the research group pioneering the Enabling Scientific Data Infrastructures field in the past two decades. The group operates at the Institute of Information Science and Technologies (ISTI), an institute of the Italian National Research Council (CNR). This invaluable environment provided a unique ground to develop and validate the theories illustrated in the thesis. Focusing on the validation, the abstract resource model has been instantiated in the gCube model of the D4Science HDI, while the transactional model has been translated in the design of the IS, successfully implemented and adopted by the same HDI. The dissertation carries innovative theoretical, methodological and analytical value in the research infrastructure field and especially in the emerging Hybrid Data Infrastructures. Importantly, this work has been validated in one of the most challenging contexts available. The thesis is organised in chapters: Chapters 1 and 2 describe the problem statement; Chapter 3 provides a state-of-the-art overview of the problem; Chapter 4 develops the theoretical framework by describing both the abstract and gCube resource models; Chapters 5 presents transaction model, how it can be used, and why it focuses on the transaction technique; Chapter 6 offers the core methodological support with the description of the IS to support the abstract resource model and the transaction model and; Chapters 7 and 8 conclude with the validation of proposed study and the contribution to the literature it provides.