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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. 15 pages, 8 tables, 3 figures

International audience; In this paper, we present an online communication-driven decision support system to align terms from a dataset with terms of another dataset (standardized controlled vocabulary or not). Heterotoki differs from existing proposals in that it takes place at the interface with humans, inviting the experts to commit on their definitions, so as to either agree to validate the mapping or to propose some enrichment to the terminologies. More precisely, differently to most of existing proposals that support terminology alignment, Heterotoki sustains the negotiation of meaning thanks to semantic coordination support within its interface design. This negotiation involves domain experts having produced multiple datasets.

Over the last decade Digital Humanities has ceased being a “niche discipline” and have become a major phenomenon in academic and cultural debate. Significant scientific results and outcomes have been achieved, and fundamental research infrastructures have been realized. Despite these far-reaching outcomes, Digital Humanities still does not have a satisfactory influence in the traditional disciplinary fields. We need to find new methods to deal with cultural artifacts and texts. Amongst the many emerging research fields in the DH, two come forth as the most promising and interesting: Big Data and distant reading; Semantic Web and Linked Open Data. In my paper I will argue that Big Data in the Humanities, although very promising, have some critical issues, and I will propose the idea of a Semantic Cultural and Literary Web, a collaborative infrastructure based on ontology driven semantic annotation of primary resources.  Over the last decade Digital Humanities has ceased being a “niche discipline” and have become a major phenomenon in academic and cultural debate. Significant scientific results and outcomes have been achieved, and fundamental research infrastructures have been realized. Despite these far-reaching outcomes, Digital Humanities still does not have a satisfactory influence in the traditional disciplinary fields. We need to find new methods to deal with cultural artifacts and texts. Amongst the many emerging research fields in the DH, two come forth as the most promising and interesting: Big Data and distant reading; Semantic Web and Linked Open Data. In my paper I will argue that Big Data in the Humanities, although very promising, have some critical issues, and I will propose the idea of a Semantic Cultural and Literary Web, a collaborative infrastructure based on ontology driven semantic annotation of primary resources.

Within the EU funded project “INCEPTION – Inclusive Cultural Heritage in Europe through 3D semantic modelling”, the use and application of H-BIM data is focused at. The project realizes innovation in 3D modelling of cultural heritage through an inclusive approach for time-dynamic 3D reconstruction of built and social environments.

Digital archives of memory institutions are typically concerned with the cataloguing of artefacts of artistic, historical, and cultural value. Recently, new forms of citizen participation in cultural heritage have emerged, producing a wealth of material spanning from visitors’ experiential feedback on exhibitions and cultural artefacts to digitally mediated interactions like the ones happening on social media platforms. Citizen curation is proposed in the context of the European project SPICE (Social Participation, Cohesion, and Inclusion through Cultural Engagement) as a methodology for producing, collecting, interpreting, and archiving people’s responses to cultural objects, with the aim of favouring the emergence of multiple, sometimes conflicting, viewpoints and motivating users and memory institutions to reflect upon them. We argue that citizen curation urges to rethink the nature of computational infrastructures supporting data management of memory institutions, bringing novel challenges that include issues of distribution, authoritativeness, interdependence, privacy, and rights management. To approach these issues, we survey relevant literature toward a distributed, Linked Data infrastructure, with a focus on identifying the roles and requirements involved in such an infrastructure. We show how existing research can contribute significantly in facing the challenges raised by citizen curation and discuss challenges and opportunities from the socio-technical standpoint.

This paper describes the achievements of the H2020 project INDIGO-DataCloud. The project has provided e-infrastructures with tools, applications and cloud framework enhancements to manage the demanding requirements of scientific communities, either locally or through enhanced interfaces. The middleware developed allows to federate hybrid resources, to easily write, port and run scientific applications to the cloud. In particular, we have extended existing PaaS (Platform as a Service) solutions, allowing public and private e-infrastructures, including those provided by EGI, EUDAT, and Helix Nebula, to integrate their existing services and make them available through AAI services compliant with GEANT interfederation policies, thus guaranteeing transparency and trust in the provisioning of such services. Our middleware facilitates the execution of applications using containers on Cloud and Grid based infrastructures, as well as on HPC clusters. Our developments are freely downloadable as open source components, and are already being integrated into many scientific applications. 39 pages, 15 figures.Version accepted in Journal of Grid Computing

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.

This paper explores key issues in the development of open access to research data. The use of digital means for developing, storing and manipulating data is creating a focus on ‘data-driven science’. One aspect of this focus is the development of ‘open access’ to research data. Open access to research data refers to the way in which various types of data are openly available to public and private stakeholders, user communities and citizens. Open access to research data, however, involves more than simply providing easier and wider access to data for potential user groups. The development of open access requires attention to the ways data are considered in different areas of research. We identify how open access is being unevenly developed across the research environment and the consequences this has in terms of generating data gaps. Data gaps refer to the way data becomes detached from published conclusions. To address these issues, we examine four main areas in developing open access to research data: stakeholder roles and values; technological requirements for managing and sharing data; legal and ethical regulations and procedures; institutional roles and policy frameworks. We conclude that problems of variability and consistency across the open access ecosystem need to be addressed within and between these areas to ensure that risks surrounding a data gap are managed in open access. 11 authors. Missing: Sally Wyatt

This article has been accepted for publication by EUP in the IJHAC: International Journal of Humanities and Arts Computing (https://www.euppublishing.com/loi/ijhac); International audience; Since the first ESFRI roadmap in 2006, multiple humanities Research Infrastructures (RIs) have been set up all over the European continent, supporting archaeologists (ARIADNE), linguists (CLARIN-ERIC), Holocaust researchers (EHRI), cultural heritage specialists (IPERION-CH) and others. These examples only scratch the surface of the breadth of research communities that have benefited from close cooperation in the European Research Area.While each field developed discipline-specific services over the years, common themes can also be distinguished. All humanities RIs address, in varying degrees, questions around research data management, the use of standards and the desired interoperability of data across disciplinary boundaries.This article sheds light on how cluster project PARTHENOS developed pooled services and shared solutions for its audience of humanities researchers, RI managers and policymakers. In a time where the convergence of existing infrastructure is becoming ever more important – with the construction of a European Open Science Cloud as an audacious, ultimate goal – we hope that our experiences inform future work and provide inspiration on how to exploit synergies in interdisciplinary, transnational, scientific cooperation.

The EU Project INCEPTION will create a platform that is able to exchange content according to state-of-the-art available open BIM standards. This INCEPTION open Heritage BIM platform is not only exchanging data according to existing state-of-the-art standards, but it is based on a new Heritage BIM model using Semantic Web technology. This allows applications to retrieve content according to modern query languages like SPARQL and allows user defined ‘on-the-fly’ extensions of the standard. This paper describes the structure and development of this new Heritage BIM standard. The Heritage BIM standard is developed by several Semantic Web and BIM standardization specialists in combination with top experts in the field of Cultural Heritage, all of them partners within the INCEPTION project.