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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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metaBUS Shiny

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metaBUS Shiny

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metaBUS Classic

Access our first platform (only ~200,000 findings; for nostalgic users)

metaBUS Classic

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Recent Publications

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