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A logic approach to modelling nomenclatural change

Authors: Franz, Nico M.; Zhang, Chao; Lee, Joohyung;

A logic approach to modelling nomenclatural change

Abstract

Abstract We utilize an Answer Set Programming (ASP) approach to show that the principles of nomenclature are tractable in computational logic. To this end we design a hypothetical, 20 nomenclatural taxon use case, with starting conditions that embody several overarching principles of the International Code of Zoological Nomenclature, including Binomial Nomenclature, Priority, Coordination, Homonymy, Typification and the structural requirement of Gender Agreement. The use case ending conditions are triggered by the reinterpretation of the diagnostic features of one of 12 type specimens anchoring the corresponding species‐level epithets. Permutations of this child‐to‐parent reassignment action lead to 36 alternative scenarios, where each scenario requires a set of 1–14 logically contingent nomenclatural emendations. We show that an ASP transition system approach can correctly infer the Code‐mandated changes for each scenario, and visually output the ending conditions. The results provide a foundation for further developing logic‐based nomenclatural change optimization and validation services, which could be applied in global nomenclatural registries. More generally, logic explorations of nomenclatural and taxonomic change scenarios provide a novel means of assessing design biases inherent in the principles of nomenclature, and can therefore inform the design of future, big data‐compatible identifier systems that recognize and mitigate these constraints.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Average
Green
hybrid