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    SAKE: A Semantic Authoring and Annotation Tool for Knowledge Extraction
    Greenhouse Gas (GHG) accounting is traditionally a lengthy and manual process that requires the expertise of experienced environmental scientists; due to the recognition of the climate crisis through upcoming regulations on GHG accounting around the planet, the demand for tools that can support these environmental experts and accelerate their work is growing considerably at the moment. GHG accounting is merely one application of automated support tools that require the preservation of expert knowledge in a machine-readable and machine-understandable format; across fields, this is highly relevant for automating processes that today can only be performed by individuals with specialized training. In this paper, we present SAKE, a Semantic Authoring and Annotation tool for Knowledge Extraction that allows domain experts with no proficiency in semantic technologies annotating domainspecific PDF files, creating a Knowledge Graph with instances of standardized (or new) ontologies. The resulting Knowledge Graph can then be integrated into systems to automate specialized processes. SAKE has been developed together with domain experts in the field of environmental science and is currently used in the scope of a joint project on GHG accounting.
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    Gaze-based Opportunistic Privacy-preserving Human-Agent Collaboration
    This paper introduces a novel system to enhance the spatiotemporal alignment of human abilities in agent-based workflows. This optimization is realized through the application of Linked Data and Semantic Web technologies and the system makes use of gaze data and contextual information. The showcased prototype demonstrates the feasibility of implementing such a system, where we specifically emphasize the system’s ability to constrain the dissemination of privacy-relevant information.
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    Scopus© Citations 7