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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
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.
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.
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