Background: Previous studies have demonstrated that the average time between the publication of an RCT to its inclusion in a systematic review is five years. With the assumption that systematic reviews/meta-analyses constitute one of the main bases for clinical practice guidelines, one could argue that this delay is affecting the provision of best care for patients in the healthcare system. Objectives: To present the combination of a computational ontology, statistical language, and corresponding Web application to streamline the standardization of RCT reporting and computation of meta-analysis parameters. Methods: Based on an existing computational ontology developed to classify clinical trials, the OntoTag application was created to facilitate the application of tags to different sections and terms of each RCT, thus facilitating the location and identification of each component of the trial. We tested this ontology with three meta-analyses evaluating the efficacy of HIV therapies (Briel et al., 2005; Nisekhe et al., 2003; Yazdanpanah et al., 2004) containing, respectively, six, fourteen, and three RCTs. Each RCT was tagged within OntoTag, processed using an XML interface with the statistical language R, and the output compared against original results obtained in the original meta-analysis. Results: OntoTag demonstrated excellent usability results among researchers using the application in terms of ease of use, interface and speed, although all the available features may not be immediately evident. Users pointed out as a limitation that it did not allow for importing PDF files. When comparing the results of the original three meta-analyses against the output generated from the processing of each of the batches of trials converted to XML files, point estimates, confidence intervals and graphical output were comparable in all but a few situations, discrepancies being attributed to assumptions in the analysis not fully described in the meta-analysis articles. Conclusions: Although currently not in production, this system has the potential to substantially improve the quality of reporting, also allowing for Cochrane members to check their own internal assumptions about the definitions of concepts in a clinical trial through the use of a computational ontology.