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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. 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

The Henri Poincaré correspondence is a corpus of letters sent and received by this mathematician. The edition of this correspondence is a long-term project begun during the 1990s. Since 1999, a website is devoted to publish online this correspondence with digitized letters. In 2017, it has been decided to reforge this website using Omeka S. This content management system offers useful services but some user needs have led to the development of an RDFS infrastructure associated to it. Approximate and explained searches are managed thanks to SPARQL query transformations. A prototype for efficient RDF annotation of this corpus (and similar corpora) has been designed and implemented. This article deals with these three research issues and how they are addressed. 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. International audience

Edmond, Fischer, Romary, and Tasovac begin this chapter by exploring what infrastructure means in different contexts before going on to consider ‘digital infrastructure’ as not only a tool that needs to be built but also understood. They examine practices and theories in an attempt to define infrastructure for the arts and humanities in the digital age: firstly, considering infrastructure as knowledge spaces; secondly, considering why the arts and humanities need research infrastructure and; thirdly, establishing why a community approach should be adopted and what baseline requirements should be met. They focus on the case study of DARIA ERIC and its dual hierarchical and marketplace structure to optimise knowledge sharing and in-flow from within its community. They argue that infrastructures today not only represent a different model for supporting knowledge creation but are also developing new models for creating knowledge. They conclude that DARIAH ERIC harnesses the best of two communities — research infrastructures as originally conceived of in the sciences, as well as the arts and humanities research base.

There is a growing need to establish domain-or discipline-specific approaches to research data sharing workflows. A defining feature of data and data workflows in the arts and humanities domain is their dependence on cultural heritage sources hosted and curated in museums, libraries, galleries and archives. A major difficulty when scholars interact with heritage data is that the nature of the cooperation between researchers and Cultural Heritage Institutions (henceforth CHIs) is often constrained by structural and legal challenges but even more by uncertainties as to the expectations of both parties. The Heritage Data Reuse Charter aims to address these by designing a common environment that will enable all the relevant actors to work together to connect and improve access to heritage data and make transactions related to the scholarly use of cultural heritage data more visible and transparent. As a first step, a wide range of stakeholders on the Cultural Heritage and research sector agreed upon a set of generic principles, summarized in the Mission Statement of the Charter, that can serve as a baseline governing the interactions between CHIs, researchers and data centres. This was followed by a long and thorough validation process related to these principles through surveys 1 and workshops 2. As a second step, we now put forward a questionnaire template tool that helps researchers and CHIs to translate the 6 core principles into specific research project settings. It contains questions about access to data, provenance information, preferred citation standards, hosting responsibilities etc. on the basis of which the parties can arrive at mutual reuse agreements that could serve as a starting point for a FAIR-by-construction data management, right from the project planning/application phase. The questionnaire template and the resulting mutual agreements can be flexibly applied to projects of different scale and in platform-independent ways. Institutions can embed them into their own exchange protocols while researchers can add them to their Data Management Plans. As such, they can show evidence for responsible and fair conduct of cultural heritage data, and fair (but also FAIR) research data management practices that are based on partnership with the holding institution.

Biased language commonly occurs around topics which are of controversial nature, thus, stirring disagreement between the different involved parties of a discussion. This is due to the fact that for language and its use, specifically, the understanding and use of phrases, the stances are cohesive within the particular groups. However, such cohesiveness does not hold across groups. In collaborative environments or environments where impartial language is desired (e.g. Wikipedia, news media), statements and the language therein should represent equally the involved parties and be neutrally phrased. Biased language is introduced through the presence of inflammatory words or phrases, or statements that may be incorrect or one-sided, thus violating such consensus. In this work, we focus on the specific case of phrasing bias, which may be introduced through specific inflammatory words or phrases in a statement. For this purpose, we propose an approach that relies on a recurrent neural networks in order to capture the inter-dependencies between words in a phrase that introduced bias. We perform a thorough experimental evaluation, where we show the advantages of a neural based approach over competitors that rely on word lexicons and other hand-crafted features in detecting biased language. We are able to distinguish biased statements with a precision of P=0.92, thus significantly outperforming baseline models with an improvement of over 30%. Finally, we release the largest corpus of statements annotated for biased language. Comment: The Twelfth ACM International Conference on Web Search and Data Mining, February 11--15, 2019, Melbourne, VIC, Australia

More and more cultural institutions use Linked Data principles to share and connect their collection metadata. In the archival field, initiatives emerge to exploit data contained in archival descriptions and adapt encoding standards to the semantic web. In this context, online authority files can be used to enrich metadata. However, relying on a decentralized network of knowledge bases such as Wikidata, DBpedia or even Viaf has its own difficulties. This paper aims to offer a critical view of these linked authority files by adopting a close-reading approach. Through a practical case study, we intend to identify and illustrate the possibilities and limits of RDF triples compared to institutions' less structured metadata. Comment: Workshop "Dariah "Trust and Understanding: the value of metadata in a digitally joined-up world" (14/05/2018, Brussels), preprint of the submission to the journal "Archives et Biblioth\`eques de Belgique"