Linking African Traditional Medicine Knowledge

Gossa Lô (1) , Victor de Boer (1) , Stefan Schlobach (1) , Gayo Diallo (2, 3)

1 VU - Vrije Universiteit Amsterdam [Amsterdam]
2 UB - Université de Bordeaux
3 Inserm (UMR 1219)

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.

Domaines: Intelligence artificielle [cs.AI]

Gossa Lô, Victor de Boer, Stefan Schlobach, Gayo Diallo. Linking African Traditional Medicine Knowledge. Semantic Web Applications and Tools for Healthcare and Life Sciences (SWAT4LS), Dec 2017, Rome, Italy. ⟨hal-01804941⟩