• DARIAH EU
• Publicationsclose
• Other research productsclose
• 2019-2023close
• Open Access close
• Article close

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

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presents Intergraph, a graph-based visual analytics technical demonstrator for the exploration and study of content in historical document collections.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.

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. Comment: 15 pages, 8 tables, 3 figures

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

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"

International audience

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.

Research and development are facilitated by sharing knowledge bases, and the innovation process benefits from collaborative efforts that involve the collective utilization of data. Until now, most companies and organizations have produced and collected various types of data, and stored them in data silos that still have to be integrated with one another in order to enable knowledge creation. For this to happen, both public and private actors must adopt a flexible approach to achieve the necessary transition to break data silos and create collaborative data sharing between data producers and users. In this paper, we investigate several factors influencing cooperative data usage and explore the challenges posed by the participation in cross-organizational data ecosystems by performing an interview study among stakeholders from private and public organizations in the context of the project IDE@S, which aims at fostering the cooperation in data science in the Austrian federal state of Styria. We highlight technological and organizational requirements of data infrastructure, expertise, and practises towards collaborative data usage.