Ontology-based knowledge discovery and sharing in bioinformatics and medical informatics: A brief survey

Abstract--Worldwide health scientists are producing, accessing, analyzing, integrating, and storing massive amounts of digital medical data daily, through observation, experimentation, and simulation. If we were able to effectively transfer and integrate data from all possible resources, then a deeper understanding of all these data sets and better exposed knowledge, along with appropriate insights and actions, would be granted. Unfortunately, in many cases, the data users are not the data producers, and they thus face challenges in harnessing data in unforeseen and unplanned ways. In order to obtain the ability to integrate heterogeneous data, and thereby efficiently revolutionize the traditional medical and biological research, new methodologies built upon the increasingly pervasive cyberinfrastructure are required to conceptualize traditional medical and biological data, and acquire the "deep" knowledge out of original data thereafter. As formal knowledge representation mo...

• Type: Conference
• Year: 2010
• Where: FSKD
• Authors: Jingshan Huang, Dejing Dou, Lei He, Pat Hayes, Jiangbo Dang
• Keywords: Better Exposed Knowledge, Data Sets, Digital Medical Data, FSKD 2010, Fuzzy Logic