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The European Holocaust Research Infrastructure (EHRI) started in October 2010 to build on a network that connects both people (Holocaust researchers, archivists, curators, librarians and digital humanists) and dispersed Holocaust source material and collections. EHRI’s aim is making sources visible in a systematic way in order to counteract the fragmentation of the sources and to reveal interconnections. EHRI focuses on Archive and collection descriptions, which are available through the EHRI Portal. EHRI is currently in its second phase and is on the ESFRI Roadmap2 for a more sustainable future. EHRI has developed a set of controlled vocabularies that serves both as a retrieval and cataloguing tool for the multilingual and highly heterogeneous data of the EHRI portal. These vocabularies were partly implemented in the first phase of the project. In the current phase of EHRI the vocabularies are in the process of quality improvement improve and enrich the existing terms, add new terms, disambiguate and remove the mistakes (deduplication, merging, adding multilingual labels, consistency checks, multiple parent relations, etc.) and increase their coverage. In the EHRI portal the subject terms are currently not available for the public, as they are used only for retrieval purposes.

AbstractThe paper presents Intergraph, a graph-based visual analytics technical demonstrator for the exploration and study of content in historical document collections. The designed prototype is motivated by a practical use case on a corpus of circa 15.000 digitized resources about European integration since 1945. The corpus allowed generating a dynamic multilayer network which represents different kinds of named entities appearing and co-appearing in the collections. To our knowledge, Intergraph is one of the first interactive tools to visualize dynamic multilayer graphs for collections of digitized historical sources. Graph visualization and interaction methods have been designed based on user requirements for content exploration by non-technical users without a strong background in network science, and to compensate for common flaws with the annotation of named entities. Users work with self-selected subsets of the overall data by interacting with a scene of small graphs which can be added, altered and compared. This allows an interest-driven navigation in the corpus and the discovery of the interconnections of its entities across time.

International audience; Current research in lifelog data has not paid enough attention to analysis of cognitive activities in comparison to physical activities. We argue that as we look into the future, wearable devices are going to be cheaper and more prevalent and textual data will play a more significant role. Data captured by lifelogging devices will increasingly include speech and text, potentially useful in analysis of intellectual activities. Analyzing what a person hears, reads, and sees, we should be able to measure the extent of cognitive activity devoted to a certain topic or subject by a learner. Test-based lifelog records can benefit from semantic analysis tools developed for natural language processing. We show how semantic analysis of such text data can be achieved through the use of taxonomic subject facets and how these facets might be useful in quantifying cognitive activity devoted to various topics in a person's day. We are currently developing a method to automatically create taxonomic topic vocabularies that can be applied to this detection of intellectual activity.

This article describes how virtual research environments (VREs) offer new opportunities for researchers to analyse open data and to obtain new insights for policy making. Although various VRE-related initiatives are under development, there is a lack of insight into how VREs support collaborative open data analysis by researchers and how this might be improved, ultimately leading to input for policy making to solve societal issues. This article clarifies in which ways VREs support researchers in open data analysis. Seven cases presenting different modes of researcher support for open data analysis were investigated and compared. Four types of support were identified: 1) ‘Figure it out yourself', 2) ‘Leading users by the hand', 3) ‘Training to provide the basics' and 4) ‘Learning from peers'. The author provides recommendations to improve the support of researchers' open data analysis and to subsequently obtain new insights for policy making to solve societal challenges.

In this article, we propose a Category Theory approach to (syntactic) interoperability between linguistic tools. The resulting category consists of textual documents, including any linguistic annotations, NLP tools that analyze texts and add additional linguistic information, and format converters. Format converters are necessary to make the tools both able to read and to produce different output formats, which is the key to interoperability. The idea behind this document is the parallelism between the concepts of composition and associativity in Category Theory with the NLP pipelines. We show how pipelines of linguistic tools can be modeled into the conceptual framework of Category Theory and we successfully apply this method to two real-life examples. Paper submitted to Applied Category Theory 2020 and accepted for Virtual Poster Session

In 2018, the European Strategic Forum for research infrastructures (ESFRI) was tasked by the Competitiveness Council, a configuration of the Council of the EU, to develop a common approach for monitoring of Research Infrastructures' performance. To this end, ESFRI established a working group, which has proposed 21 Key Performance Indicators (KPIs) to monitor the progress of the Research Infrastructures (RIs) addressed towards their objectives. The RIs were then asked to assess their relevance for their institution. The paper aims to identify the relevance of certain indicators for particular groups of RIs by using cluster and discriminant analysis. This could contribute to development of a monitoring system, tailored to particular RIs. To obtain a typology of the RIs, we first performed cluster analysis of the RIs according to their properties, which revealed clusters of RIs with similar characteristics, based on to the domain of operation, such as food, environment or engineering. Then, discriminant analysis was used to study how the relevance of the KPIs differs among the obtained clusters. This analysis revealed that the percentage of RIs correctly classified into five clusters, using the KPIs, is 80%. Such a high percentage indicates that there are significant differences in the relevance of certain indicators, depending on the ESFRI domain of the RI. The indicators therefore need to be adapted to the type of infrastructure. It is therefore proposed that the Strategic Working Groups of ESFRI addressing specific domains should be involved in the tailored development of the monitoring of pan-European RIs. 15 pages, 8 tables, 3 figures

‘Salvage’ evokes complex dynamics of loss, recovery and value, in such contexts\ud as waste management or shipwreck and maritime law. Similar dynamics, often\ud triggered by a collective or individual experience of a void or an absence, motivate\ud and inform much research into the history of women’s writing. The present article\ud explores, from the point of view of literary studies, the effects of understanding\ud research into the history of women’s writing as a salvage operation. This metaphor\ud bestows on the material studied the ambiguous status of remains. While\ud hindering the full integration of women’ s writing in more traditional accounts of\ud the literary past, the understanding of surviving material as remains can become\ud the starting point for constructing new, inclusive approaches to literary history.\ud This reframing of the problem is possible thanks to recent developments in the\ud Humanities, with an increasing interest in models and theories that allow us\ud to better understand complex and dynamic phenomena. In order to illustrate\ud the possibilities of this approach, the article draws on a brief analysis of nineteenth-century Spanish fashion magazines.

The European Holocaust Research Infrastructure (EHRI) portal website aims to aggregate digitally available archival descriptions concerning the Holocaust. This portal is actually a meta-catalogue, or an information aggregator, whose biggest goal is to have up-to-date information by means of building sustainable data pipelines between EHRI and its content providers. Just like in similar archival information aggregators (e.g. Archives Portal Europe or Monasterium), the XML-based metadata standard Encoded Archival Description (EAD) plays a key role. The article presents how EADs are imported into the portal, mainly thanks to the Open Archive Initiative protocols.

This article shows that metadata plays a central role in our society and concludes that through collaborative work, it is possible to pool solutions and to establish relationships of cooperation, both at the level of practical tool development and with regard to sharing and creating knowledge and know-how. ispartof: ABB: Archives et Bibliothèques de Belgique - Archief- en Bibliotheekwezen in België vol:106 pages:135-144 status: published

International audience