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Now showing 1 - 6 of 6
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    Towards a Representation of Temporal Data in Archival Records: Use Cases and Requirements
    (Aachen, Germany : RWTH Aachen, 2021) Bruns, Oleksandra; Tietz, Tabea; Vafaie, Mahsa; Dessì, Danilo; Sack, Harald; Lopes, Carla Teixeira; Ribeiro, Cristina; Niccolucci, Franco; Rodrigues, Irene; Freire, Nuno
    Archival records are essential sources of information for historians and digital humanists to understand history. For modern information systems they are often analysed and integrated into Knowledge Graphs for better access, interoperability and re-use. However, due to restrictions of the representation of RDF predicates temporal data within archival records is a challenge to model. This position paper explains requirements for modeling temporal data in archival records based on running research projects in which archival records are analysed and integrated in Knowledge Graphs for research and exploration.
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    Modelling Archival Hierarchies in Practice: Key Aspects and Lessons Learned
    (Aachen, Germany : RWTH Aachen, 2021) Vafaie, Mahsa; Bruns, Oleksandra; Pilz, Nastasja; Dessì, Danilo; Sack, Harald; Sumikawa, Yasunobu; Ikejiri, Ryohei; Doucet, Antoine; Pfanzelter, Eva; Hasanuzzaman, Mohammed; Dias, Gaël; Milligan, Ian; Jatowt, Adam
    An increasing number of archival institutions aim to provide public access to historical documents. Ontologies have been designed, developed and utilised to model the archival description of historical documents and to enable interoperability between different information sources. However, due to the heterogeneous nature of archives and archival systems, current ontologies for the representation of archival content do not always cover all existing structural organisation forms equallywell. After briefly contextualising the heterogeneity in the hierarchical structure of German archives, this paper describes and evaluates differences between two archival ontologies, ArDO and RiC-O, and their approaches to modelling hierarchy levels and archive dynamics.
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    Knowledge Graph enabled Curation and Exploration of Nuremberg's City Heritage
    (Aachen, Germany : RWTH Aachen, 2021) Tietz, Tabea; Bruns, Oleksandra; Göller, Sandra; Razum, Matthias; Dessì, Danilo; Sack, Harald; Paschke, Adrian; Rehm, Georg; Al Qundus, Jamal; Neudecker, Clemens; Pintscher, Lydia
    An important part in European cultural identity relies on European cities and in particular on their histories and cultural heritage. Nuremberg, the home of important artists such as Albrecht Dürer and Hans Sachs developed into the epitome of German and European culture already during the Middle Ages. Throughout history, the city experienced a number of transformations, especially with its almost complete destruction during World War 2. This position paper presents TRANSRAZ, a project with the goal to recreate Nuremberg by means of an interactive 3D tool to explore the city's architecture and culture ranging from the 17th to the 21st century. The goal of this position paper is to discuss the ongoing work of connecting heterogeneous historical data from various sources previously hidden in archives to the 3D model using knowledge graphs for a scientifically accurate interactive exploration on the Web.
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    DDB-EDM to FaBiO: The Case of the German Digital Library
    (Aachen, Germany : RWTH Aachen, 2021) Tan, Mary Ann; Tietz, Tabea; Bruns, Oleksandra; Oppenlaender, Jonas; Dessì, Danilo; Sack, Harald; Seneviratne, Oshani; Pesquita, Catia; Sequeda, Juan; Etcheverry, Lorena
    Cultural heritage portals have the goal of providing users with seamless access to all their resources. This paper introduces initial efforts for a user-oriented restructuring of the German Digital Library (DDB). At present, cultural heritage objects (CHOs) in the DDB are modeled using an extended version of the Europeana Data Model (DDBEDM), which negatively impacts usability and exploration. These challenges can be addressed by leveraging ontologies, and building a knowledge graph from the DDB's voluminous collection. Towards this goal, an alignment of bibliographic metadata from DDB-EDM to FRBR-Aligned Bibliographic Ontology (FaBiO) is presented.
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    Designing Intelligent Systems for Online Education: Open Challenges and Future Directions
    (Aachen, Germany : RWTH Aachen, 2021) Dessì, Danilo; Käser, Tanja; Marras, Mirko; Popescu, Elvira; Sack, Harald; Dessì, Danilo; Käser, Tanja; Marras, Mirko; Popescu, Elvira; Sack, Harald
    The design and delivering of platforms for online education is fostering increasingly intense research. Scaling up education online brings new emerging needs related with hardly manageable classes, overwhelming content alternatives, and academic dishonesty while interacting remotely, as examples. However, with the impressive progress of the data mining and machine learning fields, combined with the large amounts of learning-related data and high-performance computing, it has been possible to gain a deeper understanding of the nature of learning and teaching online. Methods at the analytical and algorithmic levels are constantly being developed and hybrid approaches are receiving an increasing attention. Recent methods are analyzing not only the online traces left by students a posteriori, but also the extent to which this data can be turned into actionable insights and models, to support the above needs in a computationally efficient, adaptive and timely way. In this paper, we present relevant open challenges lying at the intersection between the machine learning and educational communities, that need to be addressed to further develop the field of intelligent systems for online education. Several areas of research in this field are identified, such as data availability and sharing, time-wise and multi-modal data modelling, generalizability, fairness, explainability, interpretability, privacy, and ethics behind models delivered for supporting education. Practical challenges and recommendations for possible research directions are provided for each of them, paving the way for future advances in this field.
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    A Data Model for Linked Stage Graph and the Historical Performing Arts Domain
    (Aachen, Germany : RWTH Aachen, 2023) Tietz, Tabea; Bruns, Oleksandra; Sack, Harald; Bikakis, Antonis; Ferrario, Roberta; Jean, Stéphane; Markhoff, Béatrice; Mosca, Alessandro; Nicolosi Asmundo, Marianna
    The performing arts are complex, dynamic and embedded into societal and political systems. Providing means to research historical performing arts data is therefore crucial for understanding our history and culture. However, currently no commonly accepted ontology for historical performing arts data exists. On the example of the Linked Stage Graph, this position paper presents the ongoing process of creating an application-driven and efficient data model by leveraging and building upon existing standards and ontologies like CIDOC-CRM, FRBR, and FRBRoo.