Integrating Taxonomic Names and Concepts from Paper and Digital Sources for a New Flora of Alaska

The taxonomic foundation of a new regional flora or monograph is the reconciliation of pre-existing names and taxonomic concepts (i.e., variation in usage of those names). This reconciliation is traditionally done manually, but the availability of taxonomic resources online and of text manipulation software means that some of the work can now be automated, speeding up the development of new taxonomic products. As a contribution to developing a new Flora of Alaska (floraofalaska.org), we have digitized the main pre-existing flora (Hultén 1968) and combined it with key online taxonomic name sources (Panarctic Flora, Flora of North America, International Plant Names Index - IPNI, Tropicos, Kew’s World Checklist of Selected Plant Families), to build a canonical list of names anchored to external Globally Unique Identifiers (GUIDs) (e.g., IPNI URLs). We developed taxonomically-aware fuzzy-matching software (matchnames, Webb 2020) to identify cognates in different lists. The taxa for which there are variations between different sources in accepted names and synonyms are then flagged for review by taxonomic experts. However, even though names may be consistent across previous monographs and floras, the taxonomic concept (or circumscription) of a name may differ among authors, meaning that the way an accepted name in the flora is applied may be unfamiliar to the users of previous floras. We therefore have begun to manually align taxonomic concepts across five existing floras: Panarctic Flora, Flora of North America, Cody’s Flora of the Yukon (Cody 2000), Welsh’s Flora (Welsh 1974) and Hultén’s Flora (Hultén 1968), analysing usage and recording the Region Connection Calculus (RCC-5) relationships between taxonomic concepts common to each source. So far, we have mapped taxa in 13 genera, containing 557 taxonomic concepts and 482 taxonomic concept relationships. To facilitate this alignment process we developed software (tcm, Webb 2021) to record publications, names, taxonomic concepts and relationships, and to visualize the taxonomic concept relationships as graphs. These relationship graphs have proved to be accessible and valuable in discussing the frequently complex shifts in circumscription with the taxonomic experts who have reviewed the work. The taxonomic concept data are being integrated into the larger dataset to permit users of the new flora to instantly see both the chain of synonymy and concept map for any name. We have also worked with the developer of the Arctos Collection Management Solution (a database used for the majority of Alaskan collections) on new data tables for storage and display of taxonomic concept data. In this presentation, we will describe some of the ideas and workflows that may be of value to others working to connect across taxonomic resources.

Interval Algebra and Region Connection Calculus for Ontological Spatiotemporal Assembly Product Motion Knowledge Representation

Over the last decades, noticeable efforts have been made to construct design knowledge during the detailed geometric definition phase systematically. However, physical products exhibit functional behaviors, which explain that they evolve over space and time. Hence, there is a need to extend assembly product knowledge towards the spatiotemporal dimension to provide more realistic knowledge models in assembly design. Systematic semantic knowledge representation via ontology enables designers to understand the anticipated product’s behavior in advance. In this article, Interval Algebra (IA) and Region Connection Calculus (RCC) are investigated to formalize and construct ontological spatiotemporal assembly product motion knowledge. IA is commonly used to represent the temporality between two entities, while RCC is more appropriate to represent the ‘part-to-part’ relationships of two topological spaces. This paper discusses the roles of IA and RCC and presents a case study of a nutcracker assembly model’s behavior. The assembly product motion ontology with the aid of IA and RCC is evaluated using a task-based approach. The evaluation shows the added value of the developed ontology compared to others published in the literature.

The Automated Taxonomic Concept Reasoner

We present a visual and interactive taxonomic Artificial Intelligence (AI) tool, the Automated Taxonomic Concept Reasoner (ATCR), whose graphical web interface is under development and will also become available via an Application Programming Interface (API). The tool employs automated reasoning (Beeson 2014) to align multiple taxonomies visually, in a web browser, using user or expert-provided taxonomic articulations, i.e. "Region Connection Calculus (RCC-5) relationships between taxonomic concepts, provided in a specific logical language (Fig. 1). It does this by representing the problem of taxonomic alignment under these constraints in terms of logical inference, while performing these inferences computationally and leveraging the powerful Microsoft Z3 Satisfiability Modulo Theory (SMT) solver (de Moura and Bjørner 2008). This tool represents further development of utilities for the taxonomic concept approach, which fundamentally addresses the challenge of robust biodiversity data aggregation in light of multiple conflicting sources (and source classifications) from which primary biodiversity data almost invariably originate. The approach has proven superior to aggregation, based just on the syntax and semantics provided by the Darwin Core standard Franz and Sterner 2018). Fig. 1 provides an artificial example of such an alignment. Two taxonomies, A and B, are shown. There are five taxonomic concepts, A.One, A.Two, A.Three, B.One and B.Two. A.Two and A.Three are sub-concepts (children) of A.One, and B.Two is a sub-concept (child) of B.One. These are represented by the direction of the grey arrows. The undirected mustard-coloured lines represent relationships, i.e., the articulations referred to in the previous paragraph. These may be of five kinds: congruent (==), includes (<) and included in (>), overlap (><), and disjointness. These five relationships are known in the AI literature as the Region Connection Calculus-5 (RCC-5) (Randell et al. 1992, Bennett 1994, Bennett 1994), and taken exclusively and in conjunction with each other, have certain desirable properties with respect to the representation of spatial relationships. The provided relationship (i.e. the articulation) may also be an arbitrary disjunction of these five fundamental kinds, thus allowing for representation of some degree of logical uncertainty. Then, and under three assumptions that: "sibling" concepts are disjoint in their instances, all instances of a parent concept are instances of at least one of its child concepts, and every concept has at least one instance - the SMT-based automated reasoner is able to deduce the relationships represented by the undirected green lines. It is also able to deduce disjunctive relationships where these are logically implied. "sibling" concepts are disjoint in their instances, all instances of a parent concept are instances of at least one of its child concepts, and every concept has at least one instance - the SMT-based automated reasoner is able to deduce the relationships represented by the undirected green lines. It is also able to deduce disjunctive relationships where these are logically implied. ATCR is related to Euler/X (Franz et al. 2015), an existing tool for the same kinds of taxonomic alignment problems, which was used, for example, to obtain an alignment of two influential primate classifications (Franz et al. 2016). It differs from Euler/X in that it employs a different logical encoding that enables more efficient and more informative computational reasoning, and also in that it provides a graphical web interface, which Euler/X does not.

Descriptions of four new species ofMinyomerusHorn, 1876 sec. Jansen & Franz, 2018 (Coleoptera: Curculionidae), with notes on their distribution and phylogeny

This contribution adopts the taxonomic concept approach, including the use oftaxonomic 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 genusMinyomerusHorn, 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 ofMinyomerussec. Jansen & Franz, 2018, we describe the following four species as new to science:Minyomerus ampullaceussec. Jansen & Franz, 2018 (henceforth: [JF2018]), new species,Minyomerus franko[JF2018], new species,Minyomerus sculptilis[JF2018], new species, andMinyomerus tylotos[JF2018], new species. The four new species are added to, and integrated with, the preceding revision, and an updated key and phylogeny ofMinyomerus[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 ofMinyomerus[JF2018] with eight unreversed synapomorphies. The species-group placements, possible biogeographic origins, and natural history of the new species are discussed in detail.

Descriptions of four new species ofMinyomerusHorn, 1876 sec. Jansen & Franz, 2018 (Coleoptera: Curculionidae), with notes on their distribution and phylogeny

ABSTRACTThis contribution adopts the taxonomic concept approach, including the use oftaxonomic concept labels(name sec. [according to] source) and Region Connection Calculus (RCC-5) articulations and alignments. Prior to this study, the broad-nosed weevil genusMinyomerusHorn, 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 ofMinyomerussec. Jansen & Franz, 2018, we describe the following four species as new to science:Minyomerus ampullaceussec. Jansen & Franz, 2018 (henceforth: [JF2018]),new species,Minyomerus franko[JF2018],new species,Minyomerus sculptilis[JF2018],new species, andMinyomerus tylotos[JF2018],new species. The four new species are added to, and integrated with, the preceding revision, and an updated key and phylogeny ofMinyomerus[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 ofMinyomerus[JF2018] with eight unreversed synapomorphies. The species-group placements, possible biogeographic origins, and natural history of the new species are discussed in detail.

Leveraging Variable Elimination for Efficiently Reasoning about Qualitative Constraints

We introduce, study, and evaluate a novel algorithm in the context of qualitative constraint-based spatial and temporal reasoning that is based on the idea of variable elimination, a simple and general exact inference approach in probabilistic graphical models. Given a qualitative constraint network [Formula: see text], our algorithm utilizes a particular directional local consistency, which we denote by [Formula: see text]-consistency, in order to efficiently decide the satisfiability of [Formula: see text]. Our discussion is restricted to distributive subclasses of relations, i.e., sets of relations closed under converse, intersection, and weak composition and for which weak composition distributes over non-empty intersections for all of their relations. We demonstrate that enforcing [Formula: see text]-consistency in a given qualitative constraint network defined over a distributive subclass of relations allows us to decide its satisfiability, and obtain similar useful results for the problems of minimal labelling and redundancy. Further, we present a generic method that allows extracting a scenario from a satisfiable network, i.e., an atomic satisfiable subnetwork of that network, in a very simple and effective manner. The experimentation that we have conducted with random and real-world qualitative constraint networks defined over a distributive subclass of relations of the Region Connection Calculus and the Interval Algebra, shows that our approach exhibits unparalleled performance against state-of-the-art approaches for checking the satisfiability of such constraint networks.

Verbalizing phylogenomic conflict: Representation of node congruence across competing reconstructions of the neoavian explosion

Phylogenomic research is accelerating the publication of landmark studies that aim to resolve deep divergences of major organismal groups. Meanwhile, systems for identifying and integrating the novel products of phylogenomic inference – such as newly supported clade concepts – have not kept pace. However, the ability toverbalizeboth node concept congruence and conflict across multiple, (in effect) simultaneously endorsed phylogenomic hypotheses, is a critical prerequisite for building synthetic data environments for biological systematics, thereby also benefitting other domains impacted by these (conflicting) inferences. Here we develop a novel solution to the conflict verbalization challenge, based on a logic representation and reasoning approach that utilizes the language of Region Connection Calculus (RCC–5) to produce consistentalignmentsof node concepts endorsed by incongruent phylogenomic studies. The approach employs clade concept labels to individuate concepts used by each source, even if these carry identical names. Indirect RCC–5 modeling ofintensional(property-based) node concept definitions, facilitated by the local relaxation of coverage constraints, allows parent concepts to attain congruence in spite of their differentially sampled children. To demonstrate the feasibility of this approach, we align two recently published phylogenomic reconstructions of higher-level avian groups that entail strong conflict in the “neoavian explosion” region. According to our representations, this conflict is constituted by 26 instances of input “whole concept” overlap. These instances are further resolvable in the output labeling schemes and visualizations as “split concepts”, thereby providing the provenance services needed to build truly synthetic phylogenomic data environments. Because the RCC–5 alignments fundamentally reflect the trained, logic-enabled judgments of systematic experts, future designs for such environments need to promote a culture where experts routinely assess the intensionalities of node concepts published by our peers – even and especially when we are not in agreement with each other.

On Redundant Topological Constraints (Extended Abstract)

Redundancy checking is an important task in AI subfields such as knowledge representation and constraint solving. This paper considers redundant topological constraints, defined in the region connection calculus RCC8. We say a constraint in a set C of RCC8 constraints is redundant if it is entailed by the rest of C. A prime subnetwork of C is a subset of C which contains no redundant constraints and has the same solution set as C. It is natural to ask how to compute such a prime subnetwork, and when it is unique. While this problem is in general intractable, we show that, if S is a subalgebra of RCC8 in which weak composition distributes over nonempty intersections, then C has a unique prime subnetwork, which can be obtained in cubic time by removing all redundant constraints simultaneously from C. As a by-product, we show that any path-consistent network over such a distributive subalgebra is minimal.