Wanted: Standards for FAIR taxonomic concept representations and relationships

Making the most of biodiversity data requires linking observations of biological species from multiple sources both efficiently and accurately (Bisby 2000, Franz et al. 2016). Aggregating occurrence records using taxonomic names and synonyms is computationally efficient but known to experience significant limitations on accuracy when the assumption of one-to-one relationships between names and biological entities breaks down (Remsen 2016, Franz and Sterner 2018). Taxonomic treatments and checklists provide authoritative information about the correct usage of names for species, including operational representations of the meanings of those names in the form of range maps, reference genetic sequences, or diagnostic traits. They increasingly provide taxonomic intelligence in the form of precise description of the semantic relationships between different published names in the literature. Making this authoritative information Findable, Accessible, Interoperable, and Reusable (FAIR; Wilkinson et al. 2016) would be a transformative advance for biodiversity data sharing and help drive adoption and novel extensions of existing standards such as the Taxonomic Concept Schema and the OpenBiodiv Ontology (Kennedy et al. 2006, Senderov et al. 2018). We call for the greater, global Biodiversity Information Standards (TDWG) and taxonomy community to commit to extending and expanding on how FAIR applies to biodiversity data and include practical targets and criteria for the publication and digitization of taxonomic concept representations and alignments in taxonomic treatments, checklists, and backbones. As a motivating case, consider the abundantly sampled North American deer mouse—Peromyscus maniculatus (Wagner 1845)—which was recently split from one continental species into five more narrowly defined forms, so that the name P. maniculatus is now only applied east of the Mississippi River (Bradley et al. 2019, Greenbaum et al. 2019). That single change instantly rendered ambiguous ~7% of North American mammal records in the Global Biodiversity Information Facility (n=242,663, downloaded 2021-06-04; GBIF.org 2021) and ⅓ of all National Ecological Observatory Network (NEON) small mammal samples (n=10,256, downloaded 2021-06-27). While this type of ambiguity is common in name-based databases when species are split, the example of P. maniculatus is particularly striking for its impact upon biological questions ranging from hantavirus surveillance in North America to studies of climate change impacts upon rodent life-history traits. Of special relevance to NEON sampling is recent evidence suggesting deer mice potentially transmit SARS-CoV-2 (Griffin et al. 2021). Automating the updating of occurrence records in such cases and others will require operational representations of taxonomic concepts—e.g., range maps, reference sequences, and diagnostic traits—that are FAIR in addition to taxonomic concept alignment information (Franz and Peet 2009). Despite steady progress, it remains difficult to find, access, and reuse authoritative information about how to apply taxonomic names even when it is already digitized. It can also be difficult to tell without manual inspection whether similar types of concept representations derived from multiple sources, such as range maps or reference sequences selected from different research articles or checklists, are in fact interoperable for a particular application. The issue is therefore different from important ongoing efforts to digitize trait information in species circumscriptions, for example, and focuses on how already digitized knowledge can best be packaged to inform human experts and artifical intelligence applications (Sterner and Franz 2017). We therefore propose developing community guidelines and criteria for FAIR taxonomic concept representations as "semantic artefacts" of general relevance to linked open data and life sciences research (Le Franc et al. 2020).

Building semantic memory from embodied and distributional language experience

Humans seamlessly make sense of a rapidly changing environment, using a seemingly limitless knowledgebase to recognize and adapt to most situations we encounter. This knowledgebase is called semantic memory. Embodied cognition theories suggest that we represent this knowledge through simulation: understanding the meaning of coffee entails re-instantiating the neural states involved in touching, smelling, seeing, and drinking coffee. Distributional semantic theories suggest that we are sensitive to statistical regularities in natural language, and that a cognitive mechanism picks up on these regularities and transforms them into usable semantic representations reflecting the contextual usage of language. These appear to present contrasting views on semantic memory, but do they? Recent years have seen a push toward combining these approaches under a common framework. These hybrid approaches augment our understanding of semantic memory in important ways, but current versions remain unsatisfactory in part because they treat sensory-perceptual and distributional-linguistic data as interacting but distinct types of data that must be combined. We synthesize several approaches which, taken together, suggest that linguistic and embodied experience should instead be considered as inseparably entangled: just as sensory and perceptual systems are reactivated to understand meaning, so are experience-based representations endemic to linguistic processing; further, sensory-perceptual experience is susceptible to the same distributional principles as language experience. This conclusion produces a characterization of semantic memory that accounts for the interdependencies between linguistic and embodied data that arise across multiple timescales, giving rise to concept representations that reflect our shared and unique experiences.

Abstract Neural Representations of Category Membership beyond Information Coding Stimulus or Response

For decades, researchers have debated whether mental representations are symbolic or grounded in sensory inputs and motor programs. Certainly, aspects of mental representations are grounded. However, does the brain also contain abstract concept representations that mediate between perception and action in a flexible manner not tied to the details of sensory inputs and motor programs? Such conceptual pointers would be useful when concepts remain constant despite changes in appearance and associated actions. We evaluated whether human participants acquire such representations using fMRI. Participants completed a probabilistic concept learning task in which sensory, motor, and category variables were not perfectly coupled or entirely independent, making it possible to observe evidence for abstract representations or purely grounded representations. To assess how the learned concept structure is represented in the brain, we examined brain regions implicated in flexible cognition (e.g., pFC and parietal cortex) that are most likely to encode an abstract representation removed from sensory–motor details. We also examined sensory–motor regions that might encode grounded sensory–motor-based representations tuned for categorization. Using a cognitive model to estimate participants' category rule and multivariate pattern analysis of fMRI data, we found the left pFC and MT coded for category in the absence of information coding for stimulus or response. Because category was based on the stimulus, finding an abstract representation of category was not inevitable. Our results suggest that certain brain areas support categorization behavior by constructing concept representations in a format akin to a symbol that differs from stimulus–motor codes.

Investigating Differences in People’s Concept Representations

Semantic memory tasks can focus on intensions (features and properties) or extensions (reference and categorization). The two aspects, intension and extension, should in principle be closely related. It is in virtue of possessing the intensional properties of a concept that an individual entity will be included in the extension of that concept. For example, any feathered creature that hatches from eggs and has two legs and a beak will be a bird, and any creature lacking any of these features will be something else. There is evidence for stable individual differences in each of these tasks, but these differences do not correspond across tasks. Two further studies show that, under certain conditions, the correspondence can be demonstrated. This chapter discusses reasons for the lack of connection in terms of different systems for conceptual understanding involving similarity versus theory-based conceptualization.

Autism-Spectrum Traits Predict the Embodiment of Manipulation Knowledge about Object Concepts: Evidence from Eyetracking

Sensorimotor-based theories of cognition predict that even subtle developmental motor differences, such as those found in individuals on the autism spectrum, affect how we represent the meaning of manipulable objects (e.g., faucet). Here, we test 85 participants, who completed the Adult Autism Spectrum Quotient (to measure autism-spectrum characteristics), on a visual world experiment designed to assess conceptual representations of manipulable objects. Participants heard words referring to manually manipulable objects (e.g., faucet) while we recorded their eye movements to arrays of four objects: the named object, a related object typically manipulated similarly (e.g., jar), and two unrelated objects. Consistent with prior work, we observed more looks to the related object than to the unrelated ones (i.e., a manipulation-relatedness effect). This effect has been taken to reflect overlapping conceptual representations of objects sharing manipulation characteristics (e.g., faucet and jar) due to embodied sensorimotor properties being part of their representations. Critically, we observed that as participant-level autism-spectrum characteristics increased, manipulation-relatedness effects became smaller, whereas in control trials that included a shape (instead of manipulation) related object, relatedness effects increased. The results support the hypothesis that differences in object-concept representations on the autism spectrum emerge at least in part via differences in sensorimotor experience.

Model-based fMRI reveals co-existing specific and generalized concept representations

There has been a long-standing debate about whether categories are represented by individual category members (exemplars) or by the central tendency abstracted from individual members (prototypes). Across neuroimaging studies, there has been neural evidence for either exemplar representations or prototype representations, but not both. In the present study, we asked whether it is possible for individuals to form multiple types of category representations within a single task. We designed a categorization task to promote both exemplar and prototype representations, and we tracked their formation across learning. We found evidence for co-existing prototype and exemplar representations in brain in regions that aligned with previous studies: prototypes in ventromedial prefrontal cortex and anterior hippocampus and exemplars in inferior frontal gyrus and lateral parietal cortex. These findings show that, under the right circumstances, individuals may form representations at multiple levels of specificity, potentially facilitating a broad range of future memory-based decisions.

Abstract neural representations of category membership beyond information coding stimulus or response

For decades, researchers have debated whether mental representations are symbolic or grounded in sensory inputs and motor programs. Certainly, aspects of mental representations are grounded. However, does the brain also contain abstract concept representations that mediate between perception and action in a flexible manner not tied to the details of sensory inputs and motor programs? Such conceptual pointers would be useful when concept remain constant despite changes in appearance and associated actions. We evaluated whether human participants acquire such representations using functional magnetic resonance imaging (fMRI). Participants completed a probabilistic concept learning task in which sensory, motor, and category variables were not perfectly coupled nor entirely independent, making it possible to observe evidence for abstract representations or purely grounded representations. To assess how the learned concept structure is represented in the brain, we examined brain regions implicated in flexible cognition (e.g., prefrontal and parietal cortex) that are most likely to encode an abstract representation removed from sensory-motor details. We also examined sensory-motor regions that might encode grounded sensory-motor based representations tuned for categorization. Using a cognitive model to estimate participants’ category rule and multivariate pattern analysis of fMRI data, we found left prefrontal cortex and MT coded for category in absence of information coding for stimulus or response. Because category was based on the stimulus, finding an abstract representation of category was not inevitable. Our results suggest that certain brain areas support categorization behaviour by constructing concept representations in a format akin to a symbol that differs from stimulus-motor codes.

Jurisprudence in the Era of Change: Subject and Structure of the Discipline

The law exists in the form of institutions and in the form of representations of institutions, since the representation of something (phenomenon) has a conceptual dimension in the representation of something (concept). Representations of law and representations of law are two aspects of the expression and manifestation of the general legal reality. This, in fact, leads to a fundamental dilemma in determining the subject of legal science. This is the science of law or the science of legal science. Given that the concept of law is a theory of law developed into a system of definitions, the practical language of law finds itself in the theoretical language of jurisprudence, and vice versa. The languages in which the law operates, and the languages in which the phenomenon of law is interpreted, constitute the general object and subject of jurisprudence.Jurisprudence is a conceptual part of legal reality, both an object and a subject of legal science. The evolution of jurisprudence in the cultural-historical logic of changes in its subject and methods is the basis for changes in its disciplinary structure and connections in the general system of social and political sciences. Each cultural and historical epoch of the existence of law corresponds to its own grammar of law and its own epistemology of law, that is, its own analytical language and disciplinary format of legal knowledge. The law exists in the definitions of its concept. The concept of law has both an ontological and epistemological status. One thinks of law because it exists, and one understands the law because it is defined. Each tradition of understanding the law can be conceptually seen in the phenomenon of law that other traditions of legal understanding do not see or do not notice. The history of the development of the concept of law (conceptualization of law) contains the history of the development of legal institutions (institutionalization of law). Both components of legal reality — objective and subjective grounds and conditions for the emergence and development of the phenomenon of law live in the framework definitions of their social culture, its language and discourse. That is, they live in historical forms of awareness and understanding of one’s own law — from the law indicated in rituals, myths, signs and symbols, to the law indicated in canonical texts, doctrines and concepts; from the law of disciplinary society to the law of network communities; from the law of political domination and bureaucratic management to the law of civil communications and network agreements.

MATHEMATICS TEACHER EDUCATION AND THE FLEXIBLE USE OF TECHNOLOGIES IN DIGITAL AGE

Advantages and disadvantages of the use of digital technologies (DT) in mathematics lessons are worldwidedissussed controversially. Many empirical studies show the benefitof the use of DT in classrooms. However, despite of inspiringresults, classroom suggestions, lesson plans and research reports,the use of DT has not succeeded, as many had expected during thelast decades. One reason is or might be that we have not been ableto convince teachers and lecturers at universities of the benefit ofDT in the classrooms in a sufficient way. However, to show thisbenefit has to be a crucial goal in teacher education because it willbe a condition for preparing teachers for industrial revolution 4.0.In the following we suggest a competence model, which classifies– for a special content (like function, equation or derivative) –the relation between levels of understanding (of the concept),representations of DT and different kind of classroom activities.The flesxible use of digital technologies will be seen in relationto this competence model, results of empirical investigations willbe intergrated and examples of the use of technologies in the upcoming digital age will be given.