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    Ontology-Based Representation for Accessible OpenCourseWare Systems
    (Basel : MDPI Publ., 2018-11-29) Elias, Mirette; Lohmann, Steffen; Auer, Sören
    OpenCourseWare (OCW) systems have been established to provide open educational resources that are accessible by anyone, including learners with special accessibility needs and preferences. We need to find a formal and interoperable way to describe these preferences in order to use them in OCW systems and retrieve relevant educational resources. This formal representation should use standard accessibility definitions of OCW that can be reused by other OCW systems to represent accessibility concepts. In this article, we present an ontology to represent the accessibility needs of learners with respect to the IMS AfA specifications. The ontology definitions together with rule-based queries are used to retrieve relevant educational resources. Related to this, we developed a user interface component that enables users to create accessibility profiles representing their individual needs and preferences based on our ontology. We evaluated the approach with five examples profiles.
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    Demonstration of a customizable knowledge graph visualization framework
    (Aachen, Germany : RWTH Aachen, 2020) Wiens, Vitali; Lohmann, Steffen; Taylor, Kerry; Gonçalves, Rafael; Lecue, Freddy; Yan, Jun
    In the context of the Semantic Web, various visualization methods and tools exist. However, suitable visualizations are highly de-pendent on individual use cases and targeted user groups. Therefore, existing solutions require modifications and adjustments to meet the de-mands of other use cases and user groups. In this demo, we present an approach for a unified framework addressing customizable visual rep-resentations of knowledge graphs. Our approach refines the commonly used steps in the visualization generation process (i.e., data access, map-ping to visual primitives, and rendering) for Semantic Web contexts. Separation of concerns for individual steps and a modular and customiz-able architecture build the foundation for a pipeline-based visualization framework. The framework enables the creation and selection of the right components for the right tasks, realizing a variety of use cases and visual representations in Semantic Web contexts.