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Reconstructing the long terms evolution of science through large scale analysis of science productions

AAP ANR La Révolution numérique : rapports aux savoirs et à la culture


  • Laboratoire Informatique de Paris 6 (LIP6-UPMC, Coordinateur)
  • Institut d'Histoire et de Philosophie des Sciences et Techniques (IHPST)
  • Institut des Systèmes Complexes de Paris Ile de France (ISC-PIF)
  • Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA Rennes)

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Towards quantitative epistemology - Reconstructing the long terms evolution of science through large scale analysis of science productions

Abstract: The evolution of scientific knowledge is directly related to the history of humanity. Document archives and bibliographic sources like the “Web Of Science” or PubMed contain a valuable source for the analysis and reconstruction of this evolution. The proposed project takes as starting point the contributions of D. Chavalarias and J.P. Cointet about the analysis of the dynamicity of evolutive corpora and the automatic construction of “phylomemetic” topic lattices (as an analogy with genealogic trees of natural species). Currently existing tools are limited to the processing of medium sized collections and a non interactive usage. The expected project outcome is situated at the crossroad between Computer science and Social sciences. Our goal is to develop new highly performant tools for building phylomemetic maps of science by exploiting recent technologies for parallelizing tasks and algorithms on complex and voluminous data. These tools are conceived and validated in collaboration with experts in philosophy and history of science over large scientific archives.

Keywords : quantitative epistemology, evolution of science, topic detection, temporal alignment, big data processing, data science, big data

EPIQUE Project Description

en/site/recherche/projets/epique/start.txt · Last modified: 03/12/2019 11:23 by amann