About metaBUS
PROBLEM
- 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.
SOLUTION
- 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.
FUNDING
- National Science Foundation (NSF)
- Social Sciences and Humanities Research Council (SSHRC)
- SHRM Foundation
- Canadian Centre for Advanced Leadership in Business (CCAL)
- VCU Presidential Research Quest Fund (PeRQ)
- National Endowment for the Humanities (NEH) Digging into Data Challenge
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INTERFACE AND TUTORIALS
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