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A Machine Reading System for Assembling Synthetic Paleontological Databases

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  • Shanan E Peters
  • Ce Zhang
  • Miron Livny
  • Christopher Ré

Abstract

Many aspects of macroevolutionary theory and our understanding of biotic responses to global environmental change derive from literature-based compilations of paleontological data. Existing manually assembled databases are, however, incomplete and difficult to assess and enhance with new data types. Here, we develop and validate the quality of a machine reading system, PaleoDeepDive, that automatically locates and extracts data from heterogeneous text, tables, and figures in publications. PaleoDeepDive performs comparably to humans in several complex data extraction and inference tasks and generates congruent synthetic results that describe the geological history of taxonomic diversity and genus-level rates of origination and extinction. Unlike traditional databases, PaleoDeepDive produces a probabilistic database that systematically improves as information is added. We show that the system can readily accommodate sophisticated data types, such as morphological data in biological illustrations and associated textual descriptions. Our machine reading approach to scientific data integration and synthesis brings within reach many questions that are currently underdetermined and does so in ways that may stimulate entirely new modes of inquiry.

Suggested Citation

  • Shanan E Peters & Ce Zhang & Miron Livny & Christopher Ré, 2014. "A Machine Reading System for Assembling Synthetic Paleontological Databases," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-22, December.
  • Handle: RePEc:plo:pone00:0113523
    DOI: 10.1371/journal.pone.0113523
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    1. Wolfgang Kiessling, 2005. "Long-term relationships between ecological stability and biodiversity in Phanerozoic reefs," Nature, Nature, vol. 433(7024), pages 410-413, January.
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    1. Gregory DeAngelo & Jacob N. Shapiro & Jeffrey Borowitz & Michael Cafarella & Christopher Ré & Gary Shiffman, 2019. "Pricing risk in prostitution: Evidence from online sex ads," Journal of Risk and Uncertainty, Springer, vol. 59(3), pages 281-305, December.

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