How do scholars and the general public make use of the ever-increasing volume of information generated by social science research? With the number of studies growing rapidly, it can be difficult to summarize research findings on a given topic or even track all relevant research papers. For that reason, the notion of developing and refining automated methods for meta-analysis is compelling.
This Digging into Data project, led by Frank Bosco of Virginia Commonwealth University and Piers Steel of the University of Calgary, will contribute to the central Digging into Data aim of making it easier to access and use big data. They will do so by extracting research findings from scientific research articles, then classifying and linking these findings in a comprehensive semantic web (where online data are structured in such a way to be more easily processed and analyzed). The PIs will then make the advanced searches, analyses, and visualizations accessible to scientists and science consumers. The information will be open access and available to both the scientific community and the general public. A noteworthy goal is that the tools will provide real-time summaries of scientific literature. By automating the process of summarizing research, this project will allow users to ask and find answers to "big science" questions in real-time.
In terms of broader impacts, this project will accelerate the move from a traditional closed publication model to an advanced open, interactive, and internet-based model with potential to bridge the scientist-practitioner gap. As such, it is likely to have a significant impact on scientific communication and the use of scientific information by policymakers.
