Ontology-centric integration and navigation of the dengue literature.
Uninhibited access to the unstructured information distributed across the web and in scientific literature databases continues to be beyond the reach of scientists and health professionals. To address this challenge we have developed a literature driven, ontology-centric navigation infrastructure consisting of a content acquisition engine, a domain-specific ontology (in OWL-DL) and an ontology instantiation pipeline delivering sentences derived by domain-specific text mining. A visual query tool for reasoning over A-box instances in the populated ontology is presented and used to build conceptual queries that can be issued to the knowledgebase. We have deployed this generic infrastructure to facilitate data integration and knowledge sharing in the domain of dengue, which is one of the most prevalent viral diseases that continue to infect millions of people in the tropical and subtropical regions annually. Using our unique methodology we illustrate simplified search and discovery on dengue information derived from distributed resources and aggregated according to dengue ontology. Furthermore we apply data mining to the instantiated ontology to elucidate trends in the mentions of dengue serotypes in scientific abstracts since 1974.
Institute for Infocomm Research (I(2)R), Data Mining Department, 21, Heng Mui Keng Terrace, Singapore 119613, Singapore.
Menaka
M
Rajapakse
Rajaraman
R
Kanagasabai
Wee Tiong
WT
Ang
Anitha
A
Veeramani
Mark J
MJ
Schreiber
Christopher J O
CJ
Baker
D001185:Artificial Intelligence; D003628:Database Management Systems; D003715:Dengue / Q000453:epidemiology / Q000276:immunology / Q000503:physiopathology; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D020407:Internet; D011642:Publications; D009626:Terminology as Topic; D014584:User-Computer Interface; D018875:Vocabulary, Controlled