We review the Symbiota software platform for creating voucher-based biodiversity information portals and communities. Symbiota was originally conceived to promote small- to medium-sized, regionally and/or taxonomically themed collaborations of natural history collections. Over the past eight years the taxonomically diverse portals have grown into an important resource in North America and beyond for mobilizing, integrating, and using specimen- and observation-based occurrence records and derivative biodiversity information products. Designed to mirror the conceptual structure of traditional floras and faunas, Symbiota is exclusively web-based and employs a novel data model, information linking, and algorithms to provide highly dynamic customization. The themed portals enable meaningful access to biodiversity data for anyone from specialist to high school student. Symbiota emulates functionality of modern Content Management Systems, providing highly sophisticated yet intuitive user interfaces for data entry, batch processes, and editing. Each kind of content provision may be selectively accessed by authenticated information providers. Occupying a fairly specific niche in the biodiversity informatics arena, Symbiota provides extensive data exchange facilities and collaborates with other development projects to incorporate and not duplicate functionality as appropriate.

The sequential stages culminating in the publication of a morphological cladistic analysis of weevils in the Exophthalmus genus complex (Coleoptera: Curculionidae: Entiminae) are reviewed, with an emphasis on how early‐stage homology assessments were gradually evaluated and refined in light of intermittent phylogenetic insights. In all, 60 incremental versions of the evolving character matrix were congealed and analysed, starting with an assembly of 52 taxa and ten traditionally deployed diagnostic characters, and ending with 90 taxa and 143 characters that reflect significantly more narrow assessments of phylogenetic similarity and scope. Standard matrix properties and analytical tree statistics were traced throughout the analytical process, and series of incongruence length indifference tests were used to identify critical points of topology change among succeeding matrix versions. This kind of parsimony‐contingent rescoping is generally representative of the inferential process of character individuation within individual and across multiple cladistic analyses. The expected long‐term outcome is a maturing observational terminology in which precise inferences of homology are parsimony‐contingent, and the notions of homology and parsimony are inextricably linked. This contingent view of cladistic character individuation is contrasted with current approaches to developing phenotype ontologies based on homology‐neutral structural equivalence expressions. Recommendations are made to transparently embrace the parsimony‐contingent nature of cladistic homology.

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.

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

Classifications and phylogenetic inferences of organismal groups change in light of new insights. Over time these changes can result in an imperfect tracking of taxonomic perspectives through the re-/use of Code-compliant or informal names. To mitigate these limitations, we introduce a novel approach for aligning taxonomies through the interaction of human experts and logic reasoners. We explore the performance of this approach with the Perelleschus use case of Franz & Cardona-Duque (2013). The use case includes six taxonomies published from 1936 to 2013, 54 taxonomic concepts (i.e., circumscriptions of names individuated according to their respective source publications), and 75 expert-asserted Region Connection Calculus articulations (e.g., congruence, proper inclusion, overlap, or exclusion). An Open Source reasoning toolkit is used to analyze 13 paired Perelleschus taxonomy alignments under heterogeneous constraints and interpretations. The reasoning workflow optimizes the logical consistency and expressiveness of the input and infers the set of maximally informative relations among the entailed taxonomic concepts. The latter are then used to produce merge visualizations that represent all congruent and non-congruent taxonomic elements among the aligned input trees. In this small use case with 6-53 input concepts per alignment, the information gained through the reasoning process is on average one order of magnitude greater than in the input. The approach offers scalable solutions for tracking provenance among succeeding taxonomic perspectives that may have differential biases in naming conventions, phylogenetic resolution, ingroup and outgroup sampling, or ostensive (member-referencing) versus intensional (property-referencing) concepts and articulations.