Evidence map›Paper›PMID 34840359›Full record

ArticleScientometrics2022

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

David Chavalarias, Quentin Lobbé, Alexandre Delanoë

Abstract read
In one paragraph

Article in Scientometrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

David ChavalariasCNRS, Complex Systems Institute of Paris Île-de-France (ISC-PIF), 113 rue Nationale, 75013 Paris, France.ORCID 0000-0001-9485-1399
Quentin LobbéCNRS, Complex Systems Institute of Paris Île-de-France (ISC-PIF), 113 rue Nationale, 75013 Paris, France.
Alexandre DelanoëCNRS, Complex Systems Institute of Paris Île-de-France (ISC-PIF), 113 rue Nationale, 75013 Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

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

Identifiers

PMID34840359
PMCPMC8606253

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.