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Use of semantic technologies for the development of a dynamic trajectories generator in a Semantic Chemistry eLearning platform

ChemgaPedia is a multimedia, webbased eLearning service platform that currently contains about 18.000 pages organized in 1.700 chapters covering the complete bachelor studies in chemistry and related topics of chemistry, pharmacy, and life sciences. The eLearning encyclopedia contains some 25.000 media objects and the eLearning platform provides services such as virtual and remote labs for experiments. With up to 350.000 users per month the platform is the most frequently used scientific educational service in the German spoken Internet. In this demo we show the benefit of mapping the static eLearning contents of ChemgaPedia to a Linked Data representation for Semantic Chemistry which allows for generating dynamic eLearning paths tailored to the semantic profiles of the users.

preprint2010arXivOpen access
Richard HuberKirsten HantelmannAlexandru TodorSebastian KrebsRalf HeeseAdrian Paschke
Artificial Intelligence
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Open access6 authors1 topic
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
Citations: 0Reviews: 0Saves: 0Code: not linkedDataset: not linkedInstitutions: 0

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Richard HuberKirsten HantelmannAlexandru TodorSebastian KrebsRalf HeeseAdrian Paschke

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