DartSurvey Semantic-Based Synthetic Decision Support System DartSurvey For China Traditional Medicine

Public healthy accidents such as poisoning and acute infectious diseases cause terrible harm to public health and even disrupt normal political and economic order. Therefore, establishment of rapid, accurate, scientific and effective synthetic decision support system for public health emergencies clinical treatment is very necessary.In this paper, we design and implement a synthetic decision support system called DartSurvey for China Traditional Medicine. It aims to help the specialists to make decision, and find the most appropriate solution. DartSurvey is a semantic-based system, and we use self-defined metadata to describe the data in DartSurvey, and use RDF/OWL as the medium data model. So the data referenced by specialists in DartSurvey is more reusable. What is more, DartSurvey adopts many information analysis and decision-making methods, such as Brainstorming, Delphi method, Analytic Hierarchy Process to help the specialists to find the best solution.To replace recently widely used meaningless HTML/XHTML mark, we proposed a novel semantic-based web browse approach, which increases information for website, greatly improves browsing speed and provides broad support for semantic web development. For detailed core design and implementation, please reference my paper.We also design and implement a new tool called DartIE for complex ontology browse, inquiry and retrieval, which is used to assist in DartSurvey's semantic web browse. DartlE has very rich browsing patterns, and is able to make feedback to domain specialists with dynamic and intuitive viewers.At last, we will introduce the cooperation of DartSurvey and DartlE case by case. And DartSurvey's application in China Traditional Medicine Language System will also be covered.