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The DESIR project sets out to strengthen the sustainability of DARIAH and firmly establish it as a long-term leader and partner within arts and humanities communities. The project was designed to address six core infrastructural sustainability dimensions and one of these was dedicated to training and education, which is also one of the four pillars identified in the DARIAH Strategic Plan 2019-2026. In the framework of Work Package 7: Teaching, DESIR organised dedicated workshops in the six DARIAH accession countries (Czech Republic, Finland, Israel, Spain, Switzerland and the United Kingdom) to introduce them to the DARIAH infrastructure and related services, and to develop methodological research skills. The topic of each workshop was decided by accession countries representatives according to the training needs of the national communities of researchers in the (Digital) Humanities. Training topics varied greatly: on the one hand, some workshops had the objective to introduce participants to specific methodological research skills; on the other hand, a different approach was used, and some events focused on the infrastructural role of training and education. The workshops organised in the context of Work Package 7: Teaching are listed below:• CZECH REPUBLIC: “A series of fall tutorials 2019 organized by LINDAT/CLARIAHCZ, tutorial #3 on TEI Training”, November 28, 2019, Prague;• FINLAND: “Reuse & sustainability: Open Science and social sciences and humanities research infrastructures”, 23 October 2019, Helsinki;• ISRAEL: “Introduction to Text Encoding and Digital Editions”, 24 October 2019, Haifa;• SPAIN: “DESIR Workshop: Digital Tools, Shared Data, and Research Dissemination”, 3 July 2019, Madrid;• SWITZERLAND: “Sharing the Experience: Workflows for the Digital Humanities”, 5-6 December 2019, Neuchâtel;• UNITED KINGDOM: “Research Software Engineering for Digital Humanities: Role of Training in Sustaining Expertise”, 9 December, London.

Research e-infrastructures, digital archives and data services have become important pillars of scientific enterprise that in recent decades has become ever more collaborative, distributed and data-intensive. The archaeological research community has been an early adopter of digital tools for data acquisition, organisation, analysis and presentation of research results of individual projects. However, the provision of e-infrastructure and services for data sharing, discovery, access and re-use has lagged behind. This situation is being addressed by ARIADNE: the Advanced Research Infrastructure for Archaeological Dataset Networking in Europe. This EU-funded network has developed an e-infrastructure that enables data providers to register and provide access to their resources (datasets, collections) through the ARIADNE data portal, facilitating discovery, access and other services across the integrated resources. This article describes the current landscape of data repositories and services for archaeologists in Europe, and the issues that make interoperability between them difficult to realise. The results of the ARIADNE surveys on users' expectations and requirements are also presented. The main section of the article describes the architecture of the e-infrastructure, core services (data registration, discovery and access) and various other extant or experimental services. The on-going evaluation of the data integration and services is also discussed. Finally, the article summarises lessons learned, and outlines the prospects for the wider engagement of the archaeological research community in sharing data through ARIADNE. International 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

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

Published in OA on RESSI (http://www.ressi.ch/) on the 15.02.22. 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. International audience

Abstract 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/. H2020 Research Infrastructures http://dx.doi.org/10.13039/100010666 Georg-August-Universität Göttingen (1018)