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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"

We propose a morphologically informed model for named entity recognition, which is based on LSTM-CRF architecture and combines word embeddings, Bi-LSTM character embeddings, part-of-speech (POS) tags, and morphological information. While previous work has focused on learning from raw word input, using word and character embeddings only, we show that for morphologically rich languages, such as Bulgarian, access to POS information contributes more to the performance gains than the detailed morphological information. Thus, we show that named entity recognition needs only coarse-grained POS tags, but at the same time it can benefit from simultaneously using some POS information of different granularity. Our evaluation results over a standard dataset show sizable improvements over the state-of-the-art for Bulgarian NER. Comment: named entity recognition; Bulgarian NER; morphology; morpho-syntax

The concept of literary genre is a highly complex one: not only are different genres frequently defined on several, but not necessarily the same levels of description, but consideration of genres as cognitive, social, or scholarly constructs with a rich history further complicate the matter. This contribution focuses on thematic aspects of genre with a quantitative approach, namely Topic Modeling. Topic Modeling has proven to be useful to discover thematic patterns and trends in large collections of texts, with a view to class or browse them on the basis of their dominant themes. It has rarely if ever, however, been applied to collections of dramatic texts. In this contribution, Topic Modeling is used to analyze a collection of French Drama of the Classical Age and the Enlightenment. The general aim of this contribution is to discover what semantic types of topics are found in this collection, whether different dramatic subgenres have distinctive dominant topics and plot-related topic patterns, and inversely, to what extent clustering methods based on topic scores per play produce groupings of texts which agree with more conventional genre distinctions. This contribution shows that interesting topic patterns can be detected which provide new insights into the thematic, subgenre-related structure of French drama as well as into the history of French drama of the Classical Age and the Enlightenment. Comment: 11 figures

The digital format opens up new possibilities for interaction with monographic publications. In particular, annotation tools make it possible to broaden the discussion on the content of a book, to suggest new ideas, to report errors or inaccuracies, and to conduct open peer reviews. However, this requires the support of the users who might not yet be familiar with the annotation of digital documents. This paper will give concrete examples and recommendations for exploiting the potential of annotation in academic research and teaching. After presenting the annotation tool of Hypothesis, the article focuses on its use in the context of HIRMEOS (High Integration of Research Monographs in the European Open Science Infrastructure), a project aimed to improve the Open Access digital monograph. The general line and the aims of a post-peer review experiment with the annotation tool, as well as its usage in didactic activities concerning monographic publications are presented and proposed as potential best practices for similar annotation activities.

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 and the researchers working in CHIs (henceforth CHIs) is often constrained by structural and legal challenges but even more by uncertainties as to the expectations of both parties.This recognition led several European organizations such as APEF, CLARIN, Europeana, E-RIHS to come together and join forces under the governance of DARIAH to set up principles and mechanisms for improving the conditions for the use and re-use of cultural heritage data issued by cultural heritage institutions and studied and enriched by researchers. As a first step of this joint effort is the Heritage Data Reuse Charter (https://datacharter.hypotheses.org/) establishes 6 basic principles for improving the use and re-use of cultural heritage resources by researchers and , to help all the relevant actors to work together to connect and improve access to heritage data. These are: Reciprocity, Interoperability, Citability, Openness, Stewardship and Trustworthiness.As a further step in translating these principles to actual data workflows the survey below serves as a template to frame exchanges around cultural heritage data by enabling both Cultural Heritage Institutions, infrastructure providers and researchers and to clarify their goals at the beginning and the project, to specify 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. In practice, the survey below can be flexibly applied in platform-independent ways in exchange protocols between Cultural Heritage Institutions and researchers, Institutions who sign the Charter could use it (and expect to use such surveys) in their own exchange protocols. Another direction of future developments is to set up a platform dedicated to such exchanges. On the other hand, researchers are encouraged to contact the CHIs during the initial stages of their project in order to explain their plans and figure details of transaction together. This mutual declaration can later be a powerful component in their Data Management Plans as it shows 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. As enclosing a Research Data Management Plan to grant applications is becoming a more and more common requirement among research funders, we need to raise the funders’ awareness to the fact that such bi- or trilateral agreements and data reuse declarations among researchers, CHIs and infrastructure providers are crucial domain-specific components of FAIR data management.

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.

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

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.

This article presents a study of the French-speaking digital humanities. It is based on the experience of two research engineers from the French National Center for Scientific Research (CNRS) who have been studying these issues for the last ten years. They conducted a survey at the École Normale Supérieure (ENS-Paris) which enabled them to draw up an overview of the transformation of the profession of humanities and social sciences research engineers in the context of the digital humanities. The Digit_Hum initiative, which they run in parallel with their respective activities at the ENS, also provided information for this overview thanks to its role as a space for discussion about the digital humanities along with training and structuring of this field at the ENS and the Université Paris Sciences & Lettres (PSL). Cet article est une réflexion sur les humanités numériques en contexte francophone. Elle s’appuie sur l'expérience de deux ingénieures du Centre National de la Recherche Scientifique travaillant sur ces questions depuis une dizaine d'années. À travers l'enquête qu'elles ont menée à l'École normale supérieure (ENS-Paris), elles dressent un panorama de la transformation du métier d'ingénieur(e) en sciences humaines et sociales dans le contexte des humanités numériques. L'initiative Digit_Hum, qu'elles animent en parallèle de leurs activités respectives à l'École, nourrit également ce témoignage en constituant un espace de discussions, de formations et de structuration des humanités numériques au sein de l'ENS et de l’Université Paris Sciences & Lettres.