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Names are not good enough: Reasoning over taxonomic change in the Andropogon complex

  • Nico M. Franz(corresponding author)
    ,
  • Mingmin Chen
    ,
  • Parisa Kianmajd
    ,
  • Shizhuo Yu
    ,
  • ,
  • Alan S. Weakley
*Corresponding author for this work
  • School of Life Sciences
    ,
  • University of California, Davis
    ,
  • ,
  • University of North Carolina
    ,
  • University of Illinois Urbana-Champaign
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Abstract

We present a novel, logic-based solution to the challenge of reconciling the meanings of taxonomic names across multiple biological taxonomies. The challenge arises due to limitations inherent in using type-anchored taxonomic names as identifiers of granular semantic similarities and differences being expressed in original and revised taxonomic classifications. We address this challenge through: (1) the use of taxonomic concept labels- thereby individuating name usages according to particular sources and allowing each taxonomy to be recognized separately; (2) sets of user-provided Region Connection Calculus articulations among concepts (RCC-5: congruence, proper inclusion, inverse proper inclusion, overlap, exclusion); and (3) the use of an Answer Set Programming-based reasoning toolkit that ingests these constraints to infer and visualize consistent multi-taxonomy alignments. The feasibility of this approach is demonstrated with a use case involving pairwise alignments of 11 non-congruent classifications of Eastern United States grass entities variously assigned to the Andropogon glomeratus-virginicus 'complex' over an interval of 126 years. Analyses of name:meaning identity reveal that, on average, taxonomic names are reliable identifiers of taxonomic non-/congruence for approximately 60% of the 127 merge regions obtained in 12 pairwise alignments. The name:meaning cardinality over the entire time interval ranges from 1:6 to 4:1, with only 1:36 names attaining the semantically ideal 1:1 ratio. We discuss the applicability of the RCC-5 alignment approach in the context of achieving logic-based integration of non-/congruent taxonomic concept hierarchies in dynamic biodiversity data environments.

Bibliographic Information

Output type

Research Output:
Contribution to journal
Article
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 645-667 (23 pages)

Journal (Volume, Issue Number)

Semantic Web (Volume 7, Issue 6)

Publication milestones

  • Published - 2016

Publication status

Published - 2016

ISSN

1570-0844

Publication IDs

  • Scopus: 84991503730