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Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies.

David Chavalarias1,2, Quentin Lobbé1, Alexandre Delanoë1

  • 1CNRS, Complex Systems Institute of Paris Île-de-France (ISC-PIF), 113 rue Nationale, 75013 Paris, France.

Scientometrics
|November 29, 2021
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Summary

This study introduces phylomemies, a novel method to map the structure of science using digitized publications. Phylomemetic networks visualize these structures, offering insights into scientific knowledge dynamics and evolution.

Keywords:
Co-word analysisKnowledge dynamicsMulti-scale and multi-level complex systemsPhenomenological reconstructionPhylomemy reconstructionScience map

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Area of Science:

  • Complex systems studies
  • Bibliometrics
  • Information science

Background:

  • Mapping scientific knowledge is crucial for understanding its evolution.
  • Digitization of scientific production offers new opportunities for large-scale analysis.
  • Previous approaches lacked multi-scale and multi-level perspectives.

Purpose of the Study:

  • To formalize and reconstruct the dynamical structures of science (phylomemies).
  • To develop phylomemetic networks for visualizing scientific structures.
  • To introduce a novel algorithm for reconstructing phylomemies and networks.

Main Methods:

  • Formalizing knowledge dynamics at different levels and scales.
  • Reconstructing multi-scale, multi-level approximations of scientific structures (phylomemies).
  • Developing an algorithm for phylomemy and phylomemetic network reconstruction, including temporal clustering.

Main Results:

  • Demonstrated reconstruction of precise and concise phylomemies.
  • Introduced phylomemetic networks as graspable projections of scientific structures.
  • Developed a novel algorithm for reconstructing these structures and networks.

Conclusions:

  • Phylomemy reconstruction offers a new way to understand the organization and evolution of science.
  • Phylomemetic networks provide human-understandable visualizations of complex scientific landscapes.
  • The approach integrates user preferences via embodied cognition, balancing objectivity and subjectivity.