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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.

AbstractHow can researchers identify suitable research data repositories for the deposit of their research data? Which repository matches best the technical and legal requirements of a specific research project? For this end and with a humanities perspective the Data Deposit Recommendation Service (DDRS) has been developed as a prototype. It not only serves as a functional service for selecting humanities research data repositories but it is particularly a technical demonstrator illustrating the potential of re-using an already existing infrastructure - in this case re3data - and the feasibility to set up this kind of service for other research disciplines. The documentation and the code of this project can be found in the DARIAH GitHub repository: https://dariah-eric.github.io/ddrs/.

This report discusses the scholarly communication issues in Social Sciences and Humanities that are relevant to the future development and functioning of OPERAS. The outcomes collected here can be divided into two groups of innovations regarding 1) the operation of OPERAS, and 2) its activities. The “operational” issues include the ways in which an innovative research infrastructure should be governed (Chapter 1) as well as the business models for open access publications in Social Sciences and Humanities (Chapter 2). The other group of issues is dedicated to strategic areas where OPERAS and its services may play an instrumental role in providing, enabling, or unlocking innovation: FAIR data (Chapter 3), bibliodiversity and multilingualism in scholarly communication (Chapter 4), the future of scholarly writing (Chapter 5), and quality assessment (Chapter 6). Each chapter provides an overview of the main findings and challenges with emphasis on recommendations for OPERAS and other stakeholders like e-infrastructures, publishers, SSH researchers, research performing organisations, policy makers, and funders. Links to data and further publications stemming from work concerning particular tasks are located at the end of each chapter.

International audience; Published in OA on RESSI (http://www.ressi.ch/) at the end of Octobre 2021. We present here highlights from an enquiry on the innovations in scholarly writing in the Humanities and Social Sciences in the H2020 project OPERAS-P. This article explores the theme of Open Research Data and its role in the emergence of new models of scholarly writing. We examine more closely the obstacles and fostering conditions to the publication of research data, both from a social and a technical perspective.

How can researchers identify suitable research data repositories for the deposit of their research data? Which repository matches best the technical and legal requirements of a specific research project? For this end and with a humanities perspective the Data Deposit Recommendation Service (DDRS) has been developed as a prototype. It not only serves as a functional service for selecting humanities research data repositories but it is particularly a technical demonstrator illustrating the potential of re-using an already existing infrastructure - in this case re3data - and the feasibility to set up this kind of service for other research disciplines. The documentation and the code of this project can be found in the DARIAH GitHub repository: ​https://dariah-eric.github.io/ddrs/​.

International audience; This paper presents an attempt to provide a generic named-entity recognition and disambiguation module (NERD) called entity-fishing as a stable online service that demonstrates the possible delivery of sustainable technical services within DARIAH, the European digital research infrastructure for the arts and humanities. Deployed as part of the national infrastructure Huma-Num in France, this service provides an efficient state-of-the-art implementation coupled with standardised interfaces allowing an easy deployment on a variety of potential digital humanities contexts. Initially developed in the context of the FP9 EU project CENDARI, the software was well received by the user community and continued to be further developed within the H2020 HIRMEOS project where several open access publishers have integrated the service to their collections of published monographs as a means to enhance retrieval and access. entity-fishing implements entity extraction as well as disambiguation against Wikipedia and Wikidata entries. The service is accessible through a REST API which allows easier and seamless integration, language independent and stable convention and a widely used service-oriented architecture (SOA) design. Input and output data are carried out over a query data model with a defined structure providing flexibility to support the processing of partially annotated text or the repartition of text over several queries. The interface implements a variety of functionalities, like language recognition, sentence segmentation and modules for accessing and looking up concepts in the knowledge base. The API itself integrates more advanced contextual parametrisation or ranked outputs, allowing for the resilient integration in various possible use cases. The entity-fishing API has been used as a concrete use case to draft the experimental stand-off proposal, which has been submitted for integration into the TEI guidelines. The representation is also compliant with the Web Annotation Data Model (WADM). In this paper we aim at describing the functionalities of the service as a reference contribution to the subject of web-based NERD services. In this paper, we detail the workflow from input to output and unpack each building box in the processing flow. Besides, with a more academic approach, we provide a transversal schema of the different components taking into account non-functional requirements in order to facilitate the discovery of bottlenecks, hotspots and weaknesses. We also describe the underlying knowledge base, which is set up on the basis of Wikipedia and Wikidata content. We conclude the paper by presenting our solution for the service deployment: how and which the resources where allocated. The service has been in production since Q3 of 2017, and extensively used by the H2020 HIRMEOS partners during the integration with the publishing platforms.

The study and preservation of tangible cultural and natural heritage is a global challenge for science and society at large. The European Research Infrastructure for Heritage Science (E-RIHS) will play a leading role in research on the interpretation, preservation, documentation and management of heritage. As an interdisciplinary infrastructure, E-RIHS will interconnect knowledge and methodologies to address key scientific questions in the field of heritage as a whole. The infrastructure is built on ten core pillars. It will provide a structured and unified input of large-scale instruments, portable devices, physical and digital archives. Its implementation will focus on scientific excellence, interdisciplinarity and cooperation. In doing so, it will offer unprecedented research opportunities to a wide range of interdisciplinary scientific communities.

This paper addresses the integration of a Named Entity Recognition and Disambiguation (NERD) service within a group of open access (OA) publishing digital platforms and considers its potential impact on both research and scholarly publishing. The software powering this service, called entity-fishing, was initially developed by Inria in the context of the EU FP7 project CENDARI and provides automatic entity recognition and disambiguation using the Wikipedia and Wikidata data sets. The application is distributed with an open-source licence, and it has been deployed as a web service in DARIAH's infrastructure hosted by the French HumaNum. In the paper, we focus on the specific issues related to its integration on five OA platforms specialized in the publication of scholarly monographs in the social sciences and humanities (SSH), as part of the work carried out within the EU H2020 project HIRMEOS (High Integration of Research Monographs in the European Open Science infrastructure). In the first section, we give a brief overview of the current status and evolution of OA publications, considering specifically the challenges that OA monographs are encountering. In the second part, we show how the HIRMEOS project aims to face these challenges by optimizing five OA digital platforms for the publication of monographs from the SSH and ensuring their interoperability. In sections three and four we give a comprehensive description of the entity-fishing service, focusing on its concrete applications in real use cases together with some further possible ideas on how to exploit the annotations generated. We show that entity-fishing annotations can improve both research and publishing process. In the last chapter, we briefly present further possible application scenarios that could be made available through infrastructural projects.

Due to COVID19 pandemic, the 12th edition is cancelled. The LREC 2020 Proceedings are available at http://www.lrec-conf.org/proceedings/lrec2020/index.html; International audience; In this article, we will introduce two of the new parts of the new multi-part version of the Lexical Markup Framework (LMF) ISO standard, namely Part 3 of the standard (ISO 24613-3), which deals with etymological and diachronic data, and Part 4 (ISO 24613-4), which consists of a TEI serialisation of all of the prior parts of the model. We will demonstrate the use of both standards by describing the LMF encoding of a small number of examples taken from a sample conversion of the reference Portuguese dictionary Grande Dicionário Houaiss da Língua Portuguesa, part of a broader experiment comprising the analysis of different, heterogeneously encoded, Portuguese lexical resources. We present the examples in the Unified Modelling Language (UML) and also in a couple of cases in TEI.