Draw me Science - multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies
David Chavalarias, Quentin Lobbé, Alexandre Delanoë · INRIA a CCSD electronic archive server · 2021
The little prince asked Saint-Exupéry to draw him a sheep, but what if he had asked him to be drawn Science? How could he have done it and what could we have learned from it? In this article, we address the question of ``drawing science'' by taking advantage of the massive digitization of scientific production, and focusing on its body of knowledge. We demonstrate how we can reconstruct, from the massive digital traces of science, a reasonably precise and concise approximation of its dynamical structures that can be grasped by the human mind and explored interactively. For this purpose, we formalize the notion of level and scale of knowledge dynamics as complex systems and we introduce a new formal definition for phylomemetic networks as dynamical reconstruction of knowledge dynamics. We propose a new reconstruction algorithm for phylomemetic networks that outperforms previous ones and demonstrate how this approach also makes it possible to define a new temporal clustering on dynamical graphs. Finally, we show in case studies that this approach produces representations of knowledge dynamics close to the ones that can be obtained by synthesizing the points of view of experts on a given domain.