• DARIAH EU
• Publicationsclose
• Other research productsclose
• European Commission close
• EC|FP7 close
• EU close

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; This paper presents the work carried out within the EU Cendari project to provide an appropriate customisation of the EAG format that would fulfil the expectations of researchers in contemporary and medieval history describing where they could find collections and documents of specific interests. After describing the general data landscape that we have to deal with in the Cendari project, we specifically address the data entry and acquisition scenario to identify how this impacts on the actual data structures to be handled. We then present how we implemented such constraints by means of a full TEI/ODD specification of EAG and point out the main changes we made, which we think could also contribute to the further evolution of the EAG setting at large. We end up providing a wider picture of what we think could be the future of archival formats (EAG, EAD, EAC) if we want them to be more coherent and more sustainable at the service of both archives and researchers.

CENDARI Archival Research Guide; This Archival Research Guide (ARG) aims to provide the user with a broad overview of the Archival Directory, a key component of the CENDARI Virtual Research Environment. The CENDARI Archival Directory consists of all available data in the AtoM application (“Access to Memory”) and data in the main repository, which is derived from international or national aggregators as well as national archives or other data providers. All data, whether manually inputted via the AtoM application or collected from institutions, form together the Archival Directory. In this guide the term “Archival Directory” refers only to the application AtoM and it hence will be used in this narrow sense. The term “Archival Directory AtoM” reinforces this definition. Unlike most of the other ARGs in CENDARI, this is not a thematic overview of a historical subject but instead a practical guide to the Archival Directory AtoM’s aims and how it was created and organised.This guide will present the methodology used by researchers associated with the CENDARI project when creating archival description and archival institution entries in CENDARI. It explains how material was selected to be entered into the Archival Directory AtoM, which institutions were considered as ‘hidden archives’ by the CENDARI team, what material was not included, the limitations of the project and the future of the Archival Directory AtoM. The CENDARI Archival Directory AtoM can be accessed both directly from the website and indirectly via the link provided in the Note-Taking Environment (NTE).

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.

MIRABILE è il risultato dei processi di analisi e integrazione delle informazioni confluite nei data-base costituiti dalle singole ricerche condotte dalla SISMEL, dalla FEF e da altre istituzioni che hanno portato il loro contributo di analisi e di dati. Obiettivo di MIRABILE è fornire agli utenti della rete uno strumento informatico unitario, aperto e in costante evoluzione (sia dal punto di vista dei contenuti sia da quello tecnologico) per lo studio e la ricerca sugli autori medievali, i testi manoscritti e la loro tradizione. Si può effettuare la ricerca integrata su numerosi repertori specializzati tra cui il MEL «Medioevo latino. Bollettino bibliografico della cultura europea da Boezio a Erasmo - secoli VI-XV».

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

The CENDARI project committed in its original description of work to the production of a Business Plan (Deliverable 2.4), outlining a method statement for ensuring that the outputs of the CENDARI project would be available to future users. The project team decided to rename this deliverable the CENDARI “Sustainability Plan” and this document sets out the plan which is based upon a multidimensional conceptualisation of what CENDARI is and the value of its assets, as well as on the fundamental understanding of a digital project as useless if it does not ‘evolve and involve.’ This document presents not only the actions that have been and will continue to be taken by the CENDARI team, but also interrogates the topic of sustainability of research infrastructures