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TRAME is a research infrastructure for medieval manuscripts. The TRAME engine scans a set of sources for searched terms and retrieves links to a wide range of possible information, from simple reference, to detailed manuscript record, to full text transcriptions. Currently, it is possible to perform queries by: free-text, shelfmark, author, title, date, copyst or incipit, on more than 80 selected scholarly digital resources across EU and USA. Since 2014 September 1st, TRAME has entered a new phase and the current work is focused on: extending the meta-search approach to other web resources, leveraging the users interaction to define an ontology for medieval manuscripts, re-designing the front-end towards a new UX approach.

International audience; In this paper we describe the development and evaluation of a visual analytics tool to support historical research. Historians continuously gather data related to their scholarly research from archival visits and background search. Organising and making sense of all this data can be challenging as many historians continue to rely on analog or basic digital tools. We built an integrated note-taking environment for historians which unifies a set of func-tionalities we identified as important for historical research including editing, tagging, searching, sharing and visualization. Our approach was to involve users from the initial stage of brainstorming and requirement analysis through to design, implementation and evaluation. We report on the process and results of our work, and conclude by reflecting on our own experience in conducting user-centered visual analytics design for digital humanities.

Over the course of its four year project timeline, the CENDARI project has collected archival descriptions and metadata in various formats from a broad range of cultural heritage institutions. These data were drawn together in a single repository and are being stored there. The repository contains curated data which has been manually established by the CENDARI team as well as data acquired from small, ‘hidden’ archives in spreadsheet format or from big aggregators with advanced data exchange tools in place. While the acquisition and curation of heterogeneous data in a single repository presents a technical challenge in itself, the ingestion of data into the CENDARI repository also opens up the possibility to process and index them through data extraction, entity recognition, semantic enhancement and other transformations. In this way the CENDARI project was able to act as a bridge between cultural heritage institutions and historical researchers, insofar as it drew together holdings from a broad range of institutions and enabled the browsing of this heterogeneous content within a single search space. This paper describes a broad range of ways in which the CENDARI project acquired data from cultural heritage institutions as well as the necessary technical background. In exemplifying diverse data creation or acquisition strategies, multiple formats and technical solutions, assets and drawbacks of a repository, this “White Book” aims at providing guidance and advice as well as best practices for archivists and cultural heritage institutions collaborating or planning to collaborate with infrastructure projects.

International audience; CENDARI (Collaborative European Digital Archive Infrastructure) is a research infrastructure project aimed at integrating digital archives and resources for research on medieval and modern European history.The project brings together information and computer scientists with historians and existing historical research infrastructures (archives, libraries, other digital projects) to improve conditions for digital historical scholarship. CENDARIhas engaged in extensive networking with the archives and libraries of Europe, especially those in Eastern Europe.CENDARI is a 4-year, European-Commission-funded project led by Trinity College Dublin, in partnership with 14 institutions across 8 countries.

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

Iako u Zborniku dominiraju radovi koji se bave naučnicama u prošlosti, kao i njihovim radom, saznanjima, nedovoljnom afirmisanosšću njihovog rada, poteškoćama sa kojima su se suočavale, zbornik zaokružuju radovi koji se bave savremenom situacijom, tj. položajem žena u akademskoj zajednici danas i svim teškoćama koje i same akterke katkada teško detektuju i prepoznaju. Patrijarhalni mehanizmi prožimaju društvo u kome živimo na različitim nivoima, a sami principi koji vladaju u akademskom svetu – u kojima sve više važe pravila liberalnog kapitalizma i ideje o „upotrebljivosti“ nauke i merljivosti rezultata – cementiraju i prikrivaju davno odomaćen diskriminatorski odnos prema ženama i prema naučničkom glasu i diskursu koji odudara od dominantne paradigme. Stoga su neophodni neprekidni napori da se ženski glas u nauci čuje, a položaj naučnica stalno unapređuje i popravlja. Зборник радова Етнографског института САНУ 34 / Collection of Papers of Institute of Ethnography SASA 34

Digital history has spawned many great individual projects, and proven its value as both a methodology for the interrogation of sources and as a medium for the presentation and communication of research results. But the experiences of projects building research infrastructure for historical research raise the question of whether these methods can scale toward the realisation of historical ‘big data,’ or whether there are hindrances to this goal inherent in our current conceptualisation of the intersection between historical methods and computational ones. This paper discusses a number of the current barriers discovered by large-scale historical research infrastructure projects, including heterogeneous conceptions of what data is, hidden elements of data and the epistemics of humanities research. At the project level, these issues can be managed, but if digital history is to scale and grow to fit the infrastructural capability available to it, then a revisiting of some of the conceptual underpinnings of digital historical studies will be required.

International audience; One of the funded project proposals under DARIAH’s Open Humanities call 2015 was “Open History: Sustainable digital publishing of archival catalogues of twentieth-century history archives”. Based on the experiences of the Collaborative EuropeaN Digital Archival Research Infrastructure (CENDARI) and the European Holocaust Research Infrastructure (EHRI), the main goal of the “Open History” project was to enhance the dialogue between (meta-)data providers and research infrastructures. Integrating archival descriptions – when they were already available – held at a wide variety of twentieth-century history archives (from classic archives to memorial sites, libraries and private archives) into research infrastructures has proven to be a major challenge, which could not be done without some degree of limited to extensive pre-processing or other preparatory work. The “Open History” project organized two workshops and developed two tools: an easily accessible and general article on why the practice of standardization and sharing is important and how this can be achieved; and a model which provides checklists for self-analyses of archival institutions. The text that follows is the article we have developed. It intentionally remains at a general level, without much jargon, so that it can be easily read by those who are non-archivists or non-IT. Hence, we hope it will be easy to understand for both those who are describing the sources at various archives (with or without IT or archival sciences degrees), as well as decision-makers (directors and advisory boards) who wish to understand the benefits of investing in standardization and sharing of data. It is important to note is that this text is a first step, not a static, final result. Not all aspects about standardization and publication of (meta-)data are discussed, nor are updates or feedback mechanisms for annotations and comments discussed. The idea is that this text can be used in full or in part and that it will include further chapters and section updates as time goes by and as other communities begin using it. Some archives will read through much of these and see confirmation of what they have already been implementing; others – especially the smaller institutions, such as private memory institutions – will find this a low-key and hands-on introduction to help them in their efforts.