Linking African Traditional Medicine Knowledge
| dc.creator | Lô, Gossa | |
| dc.date.accessioned | 2025-08-29T11:05:33Z | |
| dc.date.issued | 2017-12-04 | |
| dc.description.abstract | African 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.other | hal-01804941 | |
| dc.identifier.uri | https://hal.science/hal-01804941 | |
| dc.identifier.uri | https://africarxiv.ubuntunet.net/handle/1/8949 | |
| dc.language.iso | en | |
| dc.subject | African Research | |
| dc.title | Linking African Traditional Medicine Knowledge | |
| dc.type | Academic Publication |
