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Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies
In 1751, Jean le Rond d’Alembert had a dream: “to make a genealogical or encyclopedic tree which will gather the various branches of knowledge together under a single point of view and will serve to indicate their origin and their relationships to one another”. In this paper, we address the question...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606253/ https://www.ncbi.nlm.nih.gov/pubmed/34840359 http://dx.doi.org/10.1007/s11192-021-04186-5 |
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author | Chavalarias, David Lobbé, Quentin Delanoë, Alexandre |
author_facet | Chavalarias, David Lobbé, Quentin Delanoë, Alexandre |
author_sort | Chavalarias, David |
collection | PubMed |
description | In 1751, Jean le Rond d’Alembert had a dream: “to make a genealogical or encyclopedic tree which will gather the various branches of knowledge together under a single point of view and will serve to indicate their origin and their relationships to one another”. In this paper, we address the question identifying the branches of science by taking advantage of the massive digitization of scientific production. In the framework of complex systems studies, we first formalize the notion of level and scale of knowledge dynamics. Then, we demonstrate how we can reconstruct a reasonably precise and concise multi-scale and multi-level approximation of the dynamical structures of Science: phylomemies. We introduce the notion of phylomemetic networks—projections of phylomemies in low dimensional spaces that can be grasped by the human mind—and propose a new algorithm to reconstruct both phylomemies and the associated phylomemetic networks. This algorithm offers, passing, a new temporal clustering on evolving semantic networks. Last, we show how phylomemy reconstruction can take into account users’ preferences within the framework of embodied cognition, thus defining a third way between the quest for objective “ground truth” and the ad-hoc adaptation to a particular user’s preferences. The robustness of this approach is illustrated by several case studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11192-021-04186-5. |
format | Online Article Text |
id | pubmed-8606253 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-86062532021-11-22 Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies Chavalarias, David Lobbé, Quentin Delanoë, Alexandre Scientometrics Article In 1751, Jean le Rond d’Alembert had a dream: “to make a genealogical or encyclopedic tree which will gather the various branches of knowledge together under a single point of view and will serve to indicate their origin and their relationships to one another”. In this paper, we address the question identifying the branches of science by taking advantage of the massive digitization of scientific production. In the framework of complex systems studies, we first formalize the notion of level and scale of knowledge dynamics. Then, we demonstrate how we can reconstruct a reasonably precise and concise multi-scale and multi-level approximation of the dynamical structures of Science: phylomemies. We introduce the notion of phylomemetic networks—projections of phylomemies in low dimensional spaces that can be grasped by the human mind—and propose a new algorithm to reconstruct both phylomemies and the associated phylomemetic networks. This algorithm offers, passing, a new temporal clustering on evolving semantic networks. Last, we show how phylomemy reconstruction can take into account users’ preferences within the framework of embodied cognition, thus defining a third way between the quest for objective “ground truth” and the ad-hoc adaptation to a particular user’s preferences. The robustness of this approach is illustrated by several case studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11192-021-04186-5. Springer International Publishing 2021-11-22 2022 /pmc/articles/PMC8606253/ /pubmed/34840359 http://dx.doi.org/10.1007/s11192-021-04186-5 Text en © Akadémiai Kiadó, Budapest, Hungary 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Chavalarias, David Lobbé, Quentin Delanoë, Alexandre Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies |
title | Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies |
title_full | Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies |
title_fullStr | Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies |
title_full_unstemmed | Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies |
title_short | Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies |
title_sort | draw me science: multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606253/ https://www.ncbi.nlm.nih.gov/pubmed/34840359 http://dx.doi.org/10.1007/s11192-021-04186-5 |
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