met•a•bus (ˈme-tə-ˌbəs) n. 1.
A cloud-based research synthesis platform sitting atop the world's largest collection of curated social science research findings.
There exist no search engines that contain the millions of scientific findings that have accumulated over time.
Summarizing the results of many studies’ findings is an essential scientific process. However, the process is arduous and can take years.
Current academic search engines rely on abstracts and keywords. Their search results are often incomplete.
We take a “bottom-up” approach to summarizing science: First collect and curate virtually all findings in a given area and then build platforms that allow rapid search, summary, and interaction.
Semi-automated extraction. We engineer processes to rapidly extract findings from research sources.
Deep curation. We then hand-curate and classify each finding according to a host of study characteristics (e.g., country of origin, sample type; …)
Field-level ontology. Each of the findings is manually tagged to a branching taxonomy containing all topics within a given scientific space.
Magic in the cloud. We join a massive database of research findings, R Statistics for number crunching, and user interfaces that allow exploration and summary of scientific findings at a level never before possible.
National Science Foundation (NSF)
Social Sciences and Humanities Research Council (SSHRC)
Canadian Centre for Advanced Leadership in Business (CCAL)
VCU Presidential Research Quest Fund (PeRQ)
National Endowment for the Humanities (NEH) Digging into Data Challenge