||Linking Electronic published scientific articles to Web ontologies is a cognitive tool of which its impacts and possibilities are far from being evaluated. The objective of this research is to investigate the potential of Web published scientific articles, conceived not only as texts, but also as a machine readable knowledge base, explicitly and formally related to Web-based public ontologies, that represent the assented knowledge of a specific domain. A prospective survey is developed to identify similar proposals and innovative experiences in electronically publishing scientific articles, authoring tools and citation analysis. Scientific methodology is also reviewed looking for structural characteristics of the scientific method presented in the written text of scientific articles. Experiences in developing Markup Language for some specific areas of knowledge, such as Chemical Markup Language, Mathematics Markup Language and Biology Markup Language, are also reviewed. An electronic publishing process is outlined which would permit the electronic publishing of not only scientific articles as full-texts, but would also enables an author to formalize the “deep structure” of a scientific article, containing assumptions, hypotheses, methodology, citations, datasets used, conclusions and contributions. All these elements are published as a knowledge base, using XML language, thus outlining a Sm-ML, a Scientific methodology Markup Language. Concepts expressed in the different parts of a Scientific article are to be linked to public Web ontologies, thus enabling the establishment of a formal relationship between the Scientific article specific knowledge base to ontologies like the UMLS – the Unified Medical Language System (http://www.nlm.nih.gov/pubs/factsheet/umls.html). The citations of an article are also be linked to the cited Web published scientific articles as qualified citations, in which the reasons to cite and the relationship between this specific scientific article and its citations are made explicit. The proposed model can enhances the scientific communication process, permitting semantic retrieval, critical inquiring, semantic citation, comparison, coherence verification and validating of a scientific article against public Web ontologies, which express the assented knowledge of a scientific area. The model was also conceived as the base for developing enhanced authoring and retrieval tools.