Some years ago I came across this paper in the arXiv:
David Chavalarias and Jean-Philippe Cointet (2010) The reconstruction of science phylogeny. arXiv:0904.3154v3I was intrigued by what they could possibly mean by "science phylogeny". The abstract contains this information:
We are facing a real challenge when coping with the continuous acceleration of scientific production and the increasingly changing nature of science. In this article, we extend the classical framework of co-word analysis to the study of scientific landscape evolution. Capitalizing on formerly introduced science mapping methods with overlapping clustering, we propose methods to reconstruct phylogenetic networks from successive science maps, and give insight into the various dynamics of scientific domains ... These results suggest that there exist regular patterns in the “life cycle” of scientific fields. The reconstruction of science phylogeny should improve our global understanding of science evolution and pave the way toward the development of innovative tools for our daily interactions with its productions. Over the long run, these methods should lead quantitative epistemology up to the point to corroborate or falsify theoretical models of science evolution based on large-scale phylogeny reconstruction from databases of scientific literature.The only actual description of phylogenetic methods is this:
The core question is: How can we reconstruct science dynamics through automated bottom-up analysis of scientific publications? ... The reconstruction of these inheritance patterns will be very useful to get a global overview of the activity and evolution of large scientific domains. Moreover, contrary to what is often encountered in biology, we should expect some hybridization events be- tween fields of research, which requires switching from phylogenetic trees to phylogenetic networks. Reconstructing the phylogenetic network of science consists in answering this simple question: given a scientific field CT' at period T' and a period T prior to T', from which fields at T does CT' derives its conceptual legacy? To achieve inter-temporal matching between fields, we have to find for each field at T the field or union of fields from which it inherits.When the authors formally published their work, the literature had changed, and the reference to phylogenetic networks had been replaced:
David Chavalarias, Jean-Philippe Cointet (2013) Phylomemetic patterns in science evolution — the rise and fall of scientific fields. PLOS One 8: e54847.The abstract contains this information:
We introduce an automated method for the bottom-up reconstruction of the cognitive evolution of science, based on big-data issued from digital libraries, and modeled as lineage relationships between scientific fields. We refer to these dynamic structures as phylomemetic networks or phylomemies, by analogy with biological evolution; and we show that they exhibit strong regularities, with clearly identifiable phylomemetic patterns.The explanation of phylomemetics is this:
[The] evolution of science, featuring innovations, cross-fertilization and selection, is suggestive of an analogy with the evolution of living organisms. We propose an adaptation of the concept of the phylogenetic tree, and combine it with the Richard Dawkins intuition of meme, to refer to phylomemetic networks (or phylomemy), which describes the complex dynamic structure of transformation of relations between terms. The concept of "phylomemetic network" is used by analogy to biological phylogenetic trees, which account for evolutionary relationships between genes. We do not make any assumption concerning the type of dynamics underlying the evolution and diffusion of terms. As such, contrarily to previous works in line with the memetics theory [9], which have already coined the term, we do not claim that cultural entities (memes) evolve following the same laws of selection as biological replicators (genes) do.The term "phylomemetics" was coined by:
Christopher J. Howe and Heather F. Windram (2011) Phylomemetics — evolutionary analysis beyond the gene. PLoS Biology 9: e1001069.However, you should note that Chavalarias & Cointet explicitly distance themselves from Howe & Windram's claim that cultural entities (memes) evolve following the same laws of selection as biological replicators (genes) do. They also insist upon a network representation rather than Howe & Windram's use of a tree.
The resulting networks are rather odd looking things, with multiple roots occurring at different times. There is one network for each of the selected fields of science (defined by their use of specific terminology). This is the one for the term "Gap junctions":
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