Linking African Traditional Medicine Knowledge

dc.creatorLô, Gossa
dc.date.accessioned2025-08-29T11:05:33Z
dc.date.issued2017-12-04
dc.description.abstractAfrican Traditional Medicine (ATM) is widely used in Africa as the first-line of treatment thanks to its accessibility and affordability. However, the lack of formalization of this knowledge can lead to safety issues and malpractice. This paper investigates a possible contribution of the Semantic Web in realizing the formalization and integration of ATM with data on conventional medicine (CM). As a proof of concept we convert various ATM datasets and link them to CM data. This results in a Linked ATM knowledge graph. We finally give some examples with some interesting SPARQL queries and insightful results.
dc.identifier.otherhal-01804941
dc.identifier.urihttps://hal.science/hal-01804941
dc.identifier.urihttps://africarxiv.ubuntunet.net/handle/1/8949
dc.language.isoen
dc.subjectAfrican Research
dc.titleLinking African Traditional Medicine Knowledge
dc.typeAcademic Publication

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