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This article presents an observational study of the virtual graph formed by equivalence links between agent entities across 8 knowledge bases. To evaluate the potential of this linked data graph, we measured the equivalences that it could provide for a real dataset. We crawled the virtual graph by starting from references to agents we found in descriptions of objects collected from data of cultural heritage institutions in Europeana. Our study characterizes the current virtual equivalence graph, presenting statistics about the links, their type and origin. Crawling the equivalences for agent URIs required several crawling iterations on the virtual equivalence graph. The amount of gathered equivalences grows steeply in the first 3 crawling iterations and stabilizes on the 4th iteration. VIAF was the KB with the highest number of equivalences, reaching 60.7%, and it was followed by Wikidata with 34.5%.

Manual inspection of individual user sessions provides valuable information on how users search within a collection. To support this inspection we present a session visualization tool, Metadata Augmented Graphs for User Sessions (MAGUS), representing sessions in a digital library. We evaluate MAGUS by comparing it with the more widely used table visualization in three representative tasks of increasing complexity performed by 12 professional participants. The perceived workload was a little higher for MAGUS than for the table. However, the answers provided during the tasks using MAGUS were generally more detailed using different types of arguments. These answers focused more on specific search behaviors and the parts of the collection users are interested in, using MAGUS’s visualization of the (bibliographic) metadata of clicked documents and selected facets. MAGUS allows professionals to extract more, valuable information on how users search within a collection.

This paper presents the way the joint ADBIS, TPDL and EDA 2020 conferences were organized online and the results of the participant survey conducted thereafter. We present the lessons learned from the participants' feedback., 7 pages, 16 figures

International audience; This volume contains a selection of the papers presented at all Workshops and DoctoralConsortium of the 24th East-European Conference on Advances in Databases andInformation Systems (ADBIS 2020), the 24th International Conference on Theory andPractice of Digital Libraries (TPDL 2020), and the 16th Workshop on BusinessIntelligence and Big Data (EDA 2020), held during August 25–27, 2020, in Lyon,France.

Research on database and information technologies has been rapidly evolving over the last couple of years. This evolution was lead by three major forces: Big Data, AI and Connected World that open the door to innovative research directions and challenges, yet exploiting four main areas: (i) computational and storage resource modeling and organization; (ii) new programming models, (iii) processing power and (iv) new applications that emerge related to health, environment, education, Cultural Heritage, Banking, etc. The 24th East-European Conference on Advances in Databases and Information Systems (ADBIS 2020), the 24th International Conference on Theory and Practice of Digital Libraries (TPDL 2020) and the 16th Workshop on Business Intelligence and Big Data (EDA 2020), held during August 25–27, 2020, at Lyon, France, and associated satellite events aimed at covering some emerging issues related to database and information system research in these areas. The aim of this paper is to present such events, their motivations, and topics of interest, as well as briefly outline the papers selected for presentations. The selected papers will then be included in the remainder of this volume.

National audience; Objectifs À l’ère du numérique, dans une UE où tout est dématérialisé, le retour à des objets physiques dans une activité sociale déconnectée est en décalage avec les habitudes.JADE (Jeu d’Apprentissage De l’Ergonomie) est un jeu de société de plateau coopératif pédagogique. Nous l’avons imaginé pour l’utiliser en groupe lors du TD final d’un cours d’ergonomie des logiciels, afin d’aider les étudiant‧e‧s à prendre du recul sur l’enseignement dispensé en croisant les différents concepts étudiés. En effet, à l’issue de l’UE, elles‧ils maîtrisent bien les concepts, mais continuent à avoir des difficultés à mettre en pratique les liens entre ces concepts. Une utilisation en soutien est également envisagée.Le jeu vise deux publics cible : les étudiant‧e‧s en informatique et le grand public lors de la fête de la science. Nous ciblons en priorité les étudiant‧e‧s de L2/L3 qui suivent nos cours d’ergonomie (LifIHM Interactions Homme-Machine), mais nous pourrions faire utiliser le jeu aux étudiant‧e‧s de M1 qui n’ont pas suivi d’UE équivalente dans leur université d’origine. Une utilisation du jeu en groupes mixtes en début d’année pourrait réduire cet écart et constituer une activité d’intégration intéressante. Des déclinaisons dans d’autres UE sont également envisageables.Le jeuLe plateau est constitué d’une capture d’écran de l’interface du logiciel à évaluer ergonomiquement (le jeu comportera plusieurs tels plateaux). Des symboles représentent les concepts d’ergonomie. Ils sont déclinés sur un ensemble de dés qui permettent de désigner les points à étudier dans la partie. On retrouve également ces symboles sur les jetons qui matérialisent l’application correcte ou incorrecte des concepts sur le plateau.Nous envisageons de compléter le dispositif avec des fiches-concepts comportant le nom du concept, son symbole, sa description/définition, un exemple et un contre-exemple. Ces fiches pourront pointer, grâce à des QRcodes, vers des vidéos pédagogiques associées aux concepts, réalisées par les étudiant‧e‧s dans le cadre de l’UE :https://www.youtube.com/playlist?list=PLW3hlBH7lNJJCC4C_jkc8AcwzmsOE1xym Deux exemplaires du jeu ont été réalisés et testés une première fois auprès de 73 étudiant‧e‧s.Résultats attendusNous espérons une amélioration des compétences et surtout un meilleur recul des étudiant‧e‧s, ainsi qu’un meilleur réinvestissement des compétences acquises dans les UE suivantes, en stage et ultérieurement en milieu professionnel.Nous pensons également que ce jeu de société coopératif agira, au-delà de l’UE, sur la motivation des étudiant‧e‧s et sur la cohésion de groupe et leur sentiment d’appartenance à une promotion.Projet soutenu par l’Université Lyon 1 via l’AAP Pratiques Pédagogiques Innovantes 2018

International audience

International audience

International audience; The last two decades have shown a huge interest in using Semantic Web technologies in Cultural Institutions. There are now a large number of Open Data projects such as Europeana, which aggregates millions of records, allowing us to find many relevant information. However, most of the effort to adopt Semantic Web principles has been spent in national libraries or at larger scope and most local libraries still store isolated data. Cultural information held in these local institutions is generally not available outside the library due to old-fashioned Integrated Library Systems (ILS). We advocate that improvements have to be done in the transformation and enrichment of the catalogs of any cultural institution to enhance the accessibility of data. The Syrtis project lies at the heart of the cultural heritage challenges and aims at providing relevant solutions for guiding librarians through the adoption of Semantic Web concepts. This paper presents an overview of the architecture built for the management of cultural records in the context of the Syrtis project. We also discuss briefly the current challenges faced by the project.

International audience; The Web 2.0 and the inexpensive cost of storage have pushed towards an exponential growth in the volume of collected and produced data. However, the integration of distributed and heterogeneous data sources has become the bottleneck for many applications, and it therefore still largely relies on manual tasks. One of this task, named matching or alignment, is the discovery of correspondences, i.e., semantically-equivalent elements in different data sources. Most approaches which attempt to solve this challenge face the issue of deciding whether a pair of elements is a correspondence or not, given the similarity value(s) computed for this pair. In this paper, we propose a generic and flexible framework for selecting the correspondences by relying on the discriminative similarity values for a pair. Running experiments on a public dataset has demonstrated the im-provment in terms of quality and the robustness for adding new similarity measures without user intervention for tuning.

International audience; The tremendous increase of data sources containing spatial information is bound up with the diversity of geospatial applications such as location-based services (LBS) and global positioning systems. LBS providers use maps to locate spatial entities referring to points of interest (POI), for instance restaurants or locations of events. In our study, we specifically focus on places that tourists can get through LBS. The multiplication of these providers has an impact on the quality of data: spatial entities referring to the same POI may include spatial and terminological properties with incomplete, inconsistent, inaccurate or even wrong data. Thus, entity matching approaches have been proposed to discover correspondences between spatial entities, and experimental validations are traditionally performed to demonstrate the performance of these approaches in terms of effectiveness and efficiency. However, the datasets used in these experiments are rarely available, thus limiting their reuse and a fair comparison between the proposed approaches. This paper introduces PABench, a benchmark for spatial entity matching, which is available for researchers to assess their algorithms. Our benchmark includes a taxonomy of observed differences, inconsistencies and errors, which enables the characterization of different LBS providers. PABench can provide a complete and accurate evaluation of the different aspects of spatial entity matching approaches, and also facilitate an understanding of their weaknesses and abilities with respect to spatial integration. This paper provides a conceptual platform to enable LBS interoperability.