Assessing similarity: a semantic approach to non-evolutionary comparative homology

Abstract

The concept of phylogenetic homology has been criticized of involving circular argumentation resulting from a methodological gap between its ontological definition and its empirical recognition criteria. Based on the role of similarity for the recognition of phylogenetic homologues I argue that phylogenetic homology presupposes non-evolutionary comparative homology. Due to their use of Platonic ideals, archetypes and the requirement of the a priori assumption of a stable positional reference system, pre-Darwinian notions of homology cannot be used in this context. Based on Young's concept of comparative homology, I suggest a similarity-based procedure for recognizing comparative homologues that utilizes a semantic framework. This approach circumvents the problems of the pre-Darwinian notions of comparative homology and provides the so far lacking conceptual basis for the application of recognition criteria of phylogenetic homology, adding the missing link to the logical chain for assessing phylogenetic homology and closing the methodological gap between its ontological definition and its epistemological recognition criteria. This approach to comparative homology provides an essential methodological framework for generalizing over individual organisms and identifying and demarcating anatomical structural kinds. It thus represents an important contribution to the theoretical and methodological foundation of both morphology and comparative biology.

Phenotypes in Insect Biodiversity Research

“…Reasoning across phenotype data When phenotype data are generated logically, as described above, using multiple ontologies and standards of the Semantic Web, one should be able to use the logic inherent in those ontologies for computation. Numerous real and hopeful examples of computation have been published, and they illustrate a range of possible use cases, including image management (Ramírez et al, 2007), connecting human disease phenotypes to mutant model organisms (Washington et al, 2009), species determination through successive queries (Deans et al, 2012b), enhancing taxonomic practice (Balhoff et al, 2013), understanding synapomorphies and homoplasy (Ramírez and Michalik, 2014), ontology-based partitioning for phylogenetic analysis (Tarasov and Génier, 2015), linking morphometric data to descriptions (Csösz et al, 2015), correlating phenotypes with environment (Thessen et al, 2015), a similarity-based approach for recognizing comparative homologs (Vogt, 2015), and correlating phenotypes with genetics and environment, across multiple disciplines (Deans et al, 2015).…”