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Classifications and phytogenies 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 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.

Overview. Taxonomic names are imperfect identifiers of specific and sometimes conflicting taxonomic perspectives in aggregated biodiversity data environments. The inherent ambiguities of names can be mitigated using syntactic and semantic conventions developed under the taxonomic concept approach. These include: (1) representation of taxonomic concept labels (TCLs: name sec. source) to precisely identify name usages and meanings, (2) use of parent/child relationships to assemble separate taxonomic perspectives, and (3) expert provision of Region Connection Calculus articulations (RCC–5: congruence, [inverse] inclusion, overlap, exclusion) that specify how data identified to different-sourced TCLs can be integrated. Application of these conventions greatly increases trust in biodiversity data networks, most of which promote unitary taxonomic 'syntheses' that obscure the actual diversity of expert-held views. Better design solutions allow users to control the taxonomic variable and thereby assess the robustness of their biological inferences under different perspectives. A unique constellation of prior efforts – including the powerful Symbiota collections software platform, the Euler/X multi-taxonomy alignment toolkit, and the \"Weakley Flora\" which entails 7,000 concepts and more than 75,000 RCC–5 articulations – provides the opportunity to build a first full-scale concept resolution service for SERNEC, the SouthEast Regional Network of Expertise and Collections, currently with 60 member herbaria and 2 million occurrence records. Intellectual merit. We have developed a multi-dimensional, step-wise plan to transition SERNEC's data culture from name- to concept-based practices. (1) We will engage SERNEC experts through annual, regional workshops and follow-up interactions that will foster buy-in and ultimately the completion of 12 community-identified use cases. (2). We will leverage RCC–5 data from the Weakley Flora and further development of the Euler/X logic reasoning toolkit to provide comprehensive genus- to variety-level concept alignments for at least 10 major flora treatments with highest relevance to SERNEC. The visualizations and estimated > 1 billion inferred concept-to-concept relations will effectively drive specimen data integration in the transformed portal. (3) We will expand Symbiota's taxonomy and occurrence schemas and related user interfaces to support the new concept data, including novel batch and map-based specimen determination modules, with easy output options in Darwin Core Archive format. (4) Through combinations of the new technology, enlisted taxonomic expertise, and SERNEC's large image resources, we will upgrade minimally 80% of all SERNEC specimen identifications from names to the narrowest suitable TCLs, or add \"uncertainty\" flags to specimens needing further study. (5) We will utilize the novel tools and data to demonstrate how controlling for the taxonomic variable in 12 use cases variously drives the outcomes of evolutionary, ecological, and conservation-based research hypotheses. Broader impacts. Our project is focused on just one herbarium network, but the potential impact is as wide as Darwin Core or even comparative biology. We believe that trust in networked biodiversity data depends on open and dynamic system designs, allowing expert access and resolution of multiple conflicting views that reflect the complex realities of ongoing taxonomic research. Taking well over 1 million SERNEC records from name- to TCL-resolution will show that \"big\" specimen data can pass the credibility threshold needed to validate the substantive data mobilization investment. We will mentor one postdoctoral researcher (UNC), two Ph.D. students (ASU, UIUC), and at least 15 undergraduate students (ASU). Each of our workshops will capacitate 10-15 SERNEC experts, who in turn can recruit colleagues and students at their home collections. We will incorporate the project theme and use cases into undergraduate courses taught at six institutions and reaching an estimated 300-500 students annually (10-40% minority students). At each institution, project members will make a systematic effort to recruit new students from underrepresented groups. Our group's leadership of Symbiota (with close ties to iDigBio), SERNEC, and local biodiversity projects and centers will further promote the new data culture. We will create a feature story \"Where do plant species occur?\" for ASU's popular \"Ask A Biologist\" website, and a series of undergraduate student-led \"How-To\" videos that illustrate the use case workflows, including the creation of multi-taxonomy alignments.

Background The biodiversity domain, and in particular biological taxonomy, is moving in the direction of semantization of its research outputs. The present work introduces OpenBiodiv-O, the ontology that serves as the basis of the OpenBiodiv Knowledge Management System. Our intent is to provide an ontology that fills the gaps between ontologies for biodiversity resources, such as DarwinCore-based ontologies, and semantic publishing ontologies, such as the SPAR Ontologies. We bridge this gap by providing an ontology focusing on biological taxonomy. Results OpenBiodiv-O introduces classes, properties, and axioms in the domains of scholarly biodiversity publishing and biological taxonomy and aligns them with several important domain ontologies (FaBiO, DoCO, DwC, Darwin-SW, NOMEN, ENVO). By doing so, it bridges the ontological gap across scholarly biodiversity publishing and biological taxonomy and allows for the creation of a Linked Open Dataset (LOD) of biodiversity information (a biodiversity knowledge graph) and enables the creation of the OpenBiodiv Knowledge Management System. A key feature of the ontology is that it is an ontology of the scientific process of biological taxonomy and not of any particular state of knowledge. This feature allows it to express a multiplicity of scientific opinions. The resulting OpenBiodiv knowledge system may gain a high level of trust in the scientific community as it does not force a scientific opinion on its users (e.g. practicing taxonomists, library researchers, etc.), but rather provides the tools for experts to encode different views as science progresses. Conclusions OpenBiodiv-O provides a conceptual model of the structure of a biodiversity publication and the development of related taxonomic concepts. It also serves as the basis for the OpenBiodiv Knowledge Management System.

This contribution adopts the taxonomic concept approach, including the use of taxonomic concept labels (name sec. [ according to ] source) and region connection calculus-5 (RCC–5) articulations and alignments. Prior to this study, the broad-nosed weevil genus Minyomerus Horn, 1876 sec. Jansen & Franz, 2015 (Curculionidae [non-focal]: Entiminae [non-focal]: Tanymecini [non-focal]) contained 17 species distributed throughout the desert and plains regions of North America. In this review of Minyomerus sec. Jansen & Franz, 2018, we describe the following four species as new to science: Minyomerus ampullaceus sec. Jansen & Franz, 2018 (henceforth: [JF2018]), new species, Minyomerus franko [JF2018], new species, Minyomerus sculptilis [JF2018], new species, and Minyomerus tylotos [JF2018], new species. The four new species are added to, and integrated with, the preceding revision, and an updated key and phylogeny of Minyomerus [JF2018] are presented. A cladistic analysis using 52 morphological characters of 26 terminal taxa (5/21 outgroup/ingroup) yielded a single most-parsimonious cladogram (Length = 99 steps, consistency index = 60, retention index = 80). The analysis reaffirms the monophyly of Minyomerus [JF2018] with eight unreversed synapomorphies. The species-group placements, possible biogeographic origins, and natural history of the new species are discussed in detail.

This contribution adopts the taxonomic concept annotation and alignment approach. Accordingly, and where indicated, previous and newly inferred meanings of taxonomic names are individuated according to one specific source. Articulations among these concepts and pairwise, logically consistent alignments of original and revisionary classifications are also provided, in addition to conventional nomenclatural provenance information. A phylogenetic revision of the broad-nosed weevil genera Minyomerus Horn, 1876 sec. O'Brien & Wibmer (1982), and Piscatopus Sleeper, 1960 sec. O'Brien & Wibmer (1982) (Curculionidae [non-focal]: Entiminae [non-focal]: Tanymecini [non-focal]) is presented. Prior to this study, Minyomerus sec. O'Brien & Wibmer (1982) contained seven species, whereas the monotypic Piscatopus sec. O'Brien & Wibmer (1982) was comprised solely of Piscatopus griseus Sleeper, 1960 sec. O'Brien & Wibmer (1982). We thoroughly redescribe these recognized species-level entities and furthermore describe ten species as new to science: Minyomerus bulbifrons sec. Jansen & Franz (2015) (henceforth: [JF2015]), sp. n., Minyomerus aeriballux [JF2015], sp. n., Minyomerus cracens [JF2015], sp. n., Minyomerus gravivultus [JF2015], sp. n., Minyomerus imberbus [JF2015], sp. n., Minyomerus reburrus [JF2015], sp. n., Minyomerus politus [JF2015], sp. n., Minyomerus puticulatus [JF2015], sp. n., Minyomerus rutellirostris [JF2015], sp. n., and Minyomerus trisetosus [JF2015], sp. n. A cladistic analysis using 46 morphological characters of 22 terminal taxa (5/17 outgroup/ingroup) yielded a single most-parsimonious cladogram (L = 82, CI = 65, RI = 82). The analysis strongly supports the monophyly of Minyomerus [JF2015] with eight unreversed synapomorphies, and places Piscatopus griseus sec. O'Brien & Wibmer (1982) within the genus as sister to Minyomerus rutellirostris [JF2015]. Accordingly, Piscatopus sec. Sleeper (1960), syn. n. is changed to junior synonymy of Minyomerus [JF2015], and its sole member Piscatopus griseus sec. Sleeper (1960) is moved to Minyomerus [JF2015] as Minyomerus griseus [JF2015], comb. n. In addition, the formerly designated type Minyomerus innocuus Horn, 1876 sec. Pierce (1913), syn. n. is changed to junior synonymy of Minyomerus microps (Say, 1831) [JF2015] which has priority. The genus is widespread throughout western North America, ranging from Canada to Mexico and Baja California. Apparent patterns of interspecific diversity of exterior and genitalic morphology, varying host plant ranges, overlapping and widely extending species distributions, suggest an early origin for Minyomerus [JF2015], with a diversification that likely followed the development of North American desert biomes. Three species in the genus - i.e., Minyomerus languidus Horn, 1876 [JF2015], Minyomerus microps [JF2015], and Minyomerus trisetosus [JF2015] - are putatively considered parthenogenetic.

Background Missing data is a common challenge in structured datasets, and numerous methods are available for imputing these missing values. While all of these imputation methods address the issue of incomplete data, it is important to note that some methods perform better than others in terms of their effectiveness. A thorough data analysis can help a researcher identify a given dataset’s most appropriate imputation approach, leading to more reliable analytical results. The primary objective of this study is to develop a conceptual framework that integrates various data imputation methods. Methods This study was conducted in two main steps. First, we defined the conceptual components and their interrelationships by identifying and categorizing primary concepts through a secondary analysis of our previous systematic review, which examined 58 studies to uncover influential factors for selecting optimal imputation methods. Second, we analyzed the implementation process, focusing on the properties of missing values and selecting appropriate imputation techniques while verifying the underlying assumptions according to the estimand framework from the ICH E9(R1) Guideline to ensure unbiased estimates and enhance the credibility of our findings. Results The findings from the secondary analysis suggest that the primary concepts of the developed conceptual framework directly influence the selection of appropriate imputation methods. Conclusions This integrated structure will enable researchers to select the most suitable imputation method based on the specific characteristics and conditions of the dataset under investigation. By employing the appropriate imputation method, the study aims to enhance the overall quality and trustworthiness of the analytical outcomes derived from the research dataset.

Using syntactic and semantic conventions of the taxonomic concept approach (Franz et al. 2015), we describe three newly recognized fossil broad-nosed weevils (Coleoptera: Curculionidae: Entiminae) preserved in Early Miocene amber (ca. 20.4-16.0 mya) from the Dominican Republic: Scelianoma compacta sp. n. sec. Franz & Zhang (2017) (henceforth abbreviated as [FZ2017]), Tropirhinus palpebratus sp. n. [FZ2017], and Diaprepes anticus sp. n. [FZ2017]. The taxonomic assignment of the amber inclusions is grounded in a preceding phylogenetic analysis by Franz (2012). As many as 88 of the 143 therein identified characters were coded for the fossils, whose traits are largely congruent with those present in extant congeners while also differing in ways that justify their new nomenclatural and taxonomic status. We present detailed images, descriptions, and phylogenetically informed diagnoses for the three new species-level entities, along with logically consistent Region Connection Calculus (RCC-5) alignments of the amended genus-level classifications for Scelianoma Franz and Girón 2009 [FZ2017], Tropirhinus Schoenherr 1823 [FZ2017], and Diaprepes Schoenherr 1823 [FZ2017] - in relation to 2-4 preceding classifications published in 1982-2012. The description of Scelianoma compacta [FZ2017] from Hispaniola is indicative of a more widespread historical range of Scelianoma [FZ2017] than reflected in the extant, southwestern Puerto Rican Scelianoma elydimorpha Franz and Girón 2009 sec. Franz and Girón (2009). The presence of Diaprepes anticus [FZ2017] in Hispaniola during the Early Miocene suggests an eastward directed process of island colonization and likely speciation of members of Diaprepes [FZ2017], given that most extant relatives occur throughout the Lesser Antilles. The herein presented data will facilitate more reliable reconstructions of historical biographic processes thought to have played a prominent role in the diversification of the West Indian and Neotropical mainland broad-nosed weevil lineages.

DNA–DNA hybridizations (DDH) play a key role in microbial species discrimination in cases when 16S rRNA gene sequence similarities are 97 % or higher. Using real-world 16S rRNA gene sequences and DDH data, we here re-investigate whether or not, and in which situations, this threshold value might be too conservative. Statistical estimates of these thresholds are calculated in general as well as more specifically for a number of phyla that are frequently subjected to DDH. Among several methods to infer 16S gene sequence similarities investigated, most of those routinely applied by taxonomists appear well suited for the task. The effects of using distinct DDH methods also seem to be insignificant. Depending on the investigated taxonomic group, a threshold between 98.2 and 99.0 % appears reasonable. In that way, up to half of the currently conducted DDH experiments could safely be omitted without a significant risk for wrongly differentiated species.

Class imbalance poses new challenges when it comes to classifying data streams. Many algorithms recently proposed in the literature tackle this problem using a variety of data-level, algorithm-level, and ensemble approaches. However, there is a lack of standardized and agreed-upon procedures and benchmarks on how to evaluate these algorithms. This work proposes a standardized, exhaustive, and comprehensive experimental framework to evaluate algorithms in a collection of diverse and challenging imbalanced data stream scenarios. The experimental study evaluates 24 state-of-the-art data streams algorithms on 515 imbalanced data streams that combine static and dynamic class imbalance ratios, instance-level difficulties, concept drift, real-world and semi-synthetic datasets in binary and multi-class scenarios. This leads to a large-scale experimental study comparing state-of-the-art classifiers in the data stream mining domain. We discuss the advantages and disadvantages of state-of-the-art classifiers in each of these scenarios and we provide general recommendations to end-users for selecting the best algorithms for imbalanced data streams. Additionally, we formulate open challenges and future directions for this domain. Our experimental framework is fully reproducible and easy to extend with new methods. This way, we propose a standardized approach to conducting experiments in imbalanced data streams that can be used by other researchers to create complete, trustworthy, and fair evaluation of newly proposed methods. Our experimental framework can be downloaded from https://github.com/canoalberto/imbalanced-streams .