Data from: Two influential primate classifications logically aligned Article Swipe

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Nico M. Franz , Naomi M. Pier , DeeAnn M. Reeder , Mingmin Chen , Shizhuo Yu , Parisa Kianmajd , Shawn Bowers , Bertram Ludaescher ·

YOU? · · 2016 · Open Access · · DOI: https://doi.org/10.5061/dryad.6jg71

Classifications and phylogenies of perceived natural entities change in the light of new evidence. Taxonomic changes, translated into Code-compliant names, frequently lead to name:meaning dissociations across succeeding treatments. Classification standards such as the Mammal Species of the World (MSW) may experience significant levels of taxonomic change from one edition to the next, with potential costs to long-term, large-scale information integration. This circumstance challenges the biodiversity and phylogenetic data communities to express taxonomic congruence and incongruence in ways that both humans and machines can process, that is, to logically represent taxonomic alignments across multiple classifications. We demonstrate that such alignments are feasible for two classifications of primates corresponding to the second and third MSW editions. Our approach has three main components: (i) use of taxonomic concept labels, that is name sec. author (where sec. means according to), to assemble each concept hierarchy separately via parent/child relationships; (ii) articulation of select concepts across the two hierarchies with user-provided Region Connection Calculus (RCC-5) relationships; and (iii) the use of an Answer Set Programming toolkit to infer and visualize logically consistent alignments of these input constraints. Our use case entails the Primates sec. Groves (1993; MSW2–317 taxonomic concepts; 233 at the species level) and Primates sec. Groves (2005; MSW3–483 taxonomic concepts; 376 at the species level). Using 402 RCC-5 input articulations, the reasoning process yields a single, consistent alignment and 153,111 Maximally Informative Relations that constitute a comprehensive meaning resolution map for every concept pair in the Primates sec. MSW2/MSW3. The complete alignment, and various partitions thereof, facilitate quantitative analyses of name:meaning dissociation, revealing that nearly one in three taxonomic names are not reliable across treatments—in the sense of the same name identifying congruent taxonomic meanings. The RCC-5 alignment approach is potentially widely applicable in systematics and can achieve scalable, precise resolution of semantically evolving name usages in synthetic, next-generation biodiversity, and phylogeny data platforms.

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Artificial Intelligence

Biology

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Primate Geography Computer science Cartography Evolutionary biology Data science Artificial intelligence Biology Paleontology

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Type: dataset
Language: en
Landing Page: https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:93645
OA Status: green
OpenAlex ID: https://openalex.org/W2950682080

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OpenAlex ID: https://openalex.org/W2950682080

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DOI: https://doi.org/10.5061/dryad.6jg71

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Title: Data from: Two influential primate classifications logically aligned

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Language: en

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Publication year: 2016

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Publication date: 2016-03-11

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Authors: Nico M. Franz, Naomi M. Pier, DeeAnn M. Reeder, Mingmin Chen, Shizhuo Yu, Parisa Kianmajd, Shawn Bowers, Bertram Ludaescher

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Landing page: https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:93645

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Open access: Yes

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OA status: green

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OA URL: https://doi.org/10.5061/dryad.6jg71

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Concepts: Primate, Geography, Computer science, Cartography, Evolutionary biology, Data science, Artificial intelligence, Biology, Paleontology

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