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If citation is a common practice for publications, it is relatively new for data especially in SSH. This paper will present the work carried out during the SSHOC project about data citation in general and more precisely how to make them actionable. International audience

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.

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. International audience

Le quartier de Renancourt, situé à l’ouest de la ville d’Amiens, est connu dans la littérature archéologique depuis le début du XXe siècle par les travaux de V. Commont. Jusqu’à une date récente, ce gisement de plein air est resté l’un des rares témoignages du Paléolithique supérieur ancien pour l’ensemble de la région loessique du nord de la France. En 2011, une nouvelle concentration de vestiges, découverte à proximité immédiate des premières fouilles de V. Commont a été mise au jour lors d’un diagnostic archéologique lié à un projet d’aménagement. Ce gisement, désormais appelé Amiens-Renancourt 1, fait l’objet depuis 2014 de campagnes de fouilles programmées annuelles.L’occupation archéologique, située à 4 m de profondeur, est datée de 23000 BP, soit aux alentours de 27 000 ans cal. BP. Aux vestiges classiques et fréquents pour les gisements paléolithiques (industrie lithique, restes osseux, etc…) s’ajoute la découverte exceptionnelle de plusieurs statuettes féminines et d’éléments de parure en craie. La rareté et le nombre important (une quinzaine de statuettes à ce jour) de ces objets nous a incité à créer en 2016 un Projet Collectif de Recherche dédié, soutenu par le Service Régional de l’Archéologie des Hauts-de-France. Un des axes de ce projet a pour ambition la numérisation de l’ensemble des statuettes à des fins multiples : d’étude scientifique, de préservation, de muséographie et de valorisation.Le poster que nous soumettons vise à présenter les choix méthodologiques effectués pour mener à bien la numérisation, les difficultés techniques rencontrées dues notamment aux très petites dimensions des certaines statuettes et les résultats déjà obtenus et attendus. C’est in fine le cahier des charges du volet modélisation tri-dimensionnelle du projet qui sera présenté, incrémenté du retour d’expérience acquis lors des premières modélisations et impressions de Vénus, et des exploitations et des explorations actuelles et envisagées des modèles. National audience

The CENDARI infrastructure is a research-supporting platform designed to provide tools for transnational historical research, focusing on two topics: medieval culture and World War I. It exposes to the end users modern Web-based tools relying on a sophisticated infrastructure to collect, enrich, annotate, and search through large document corpora. Supporting researchers in their daily work is a novel concern for infrastructures. We describe how we gathered requirements through multiple methods to understand historians' needs and derive an abstract workflow to support them. We then outline the tools that we have built, tying their technical descriptions to the user requirements. The main tools are the note-taking environment and its faceted search capabilities; the data integration platform including the Data API, supporting semantic enrichment through entity recognition; and the environment supporting the software development processes throughout the project to keep both technical partners and researchers in the loop. The outcomes are technical together with new resources developed and gathered, and the research workflow that has been described and documented. International audience

International audience