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Information in the World Wide Web accumulates rapidly with increasing rate. The size of the internet was increased by 37% within 2013, with more than 8∙108 web sites recorded (http://www.cdc.gov). Furthermore, because of the widespread antibiotic resistance to infections, the prevention of prescription drug abuse and overdose is significant. The acceleration of biological science capabilities raises bioethical questions, and the risk of inadvertent or intentional release of pathogens is high.
Figure 1. Semantic web is connecting global biomedical challenges to current biomedical approaches
Mortality of women and children in low and middle income countries account for over 95% of all maternal and child deaths because of the lack of sanitary conditions. The high occurrence of non-transmittable diseases like cardiovascular disease, cancer, diabetes, chronic respiratory disease are the predominant etiology of human mortality worldwide because of life-style, toxic substance contamination and environmental pollution (http://www.who.int). In their fight against human disease, biomedical researchers and clinicians hold a variety of modern and old fashion interdisciplinary tools. Genomics, proteomics, systems biology, molecular biology, novel vaccines and target designed chemical drugs, novel surgical therapeutic protocols and implantable devices data aggregate in the World Wide Web with exponential growth.
Integration of all these sources of information is a difficult task, and the Semantic web may be the only answer, as it is evident by the converging trends of standard literature and semantic information queries in the last ten years (See Figure 2). Indeed, semantic web services offer to the end user a reliable set of analytical instruments by gathering and evaluating computer readable data and deliver them in the form of human readable information. Semantic Web services are standing on top of classical web services and the Semantic Web markup, utilizing static resources of World Wide Web sites and transforming them to dynamic resources with interoperable semantics. Therefore, it is anticipated that utilization of this system of data analysis would offer to the scientific community a powerful tool for depositing, organizing, handling and extracting biomedical information.