Representing and coding the knowledge embedded in texts of Health Science Web published articles

Despite the fact that electronic publishing is a common activity to scholars electronic journals are still based in the print model and do not take full advantage of the facilities offered by the Semantic Web environment. This is a report of the results of a research project with the aim of investigating the possibilities of electronic publishing journal articles both as text for human reading and in machine readable format recording the new knowledge contained in the article. This knowledge is identified with the scientific methodology elements such as problem, methodology, hypothesis, results, and conclusions. A model integrating all those elements is proposed which makes explicit and records the knowledge embedded in the text of scientific articles as an ontology. Knowledge thus represented enables its processing by intelligent software agents The proposed model aims to take advantage of these facilities enabling semantic retrieval and validation of the knowledge contained in articles. To validate and enhance the model a set of electronic journal articles were analyzed