The need for data standards in zoomorphology

Anatomy and the type concept in biology show that ontologies must be adapted to the diagnostic needs of research

BACKGROUND

In times of exponential data growth in the life sciences, machine-supported approaches are becoming increasingly important and with them the need for FAIR (Findable, Accessible, Interoperable, Reusable) and eScience-compliant data and metadata standards. Ontologies, with their queryable knowledge resources, play an essential role in providing these standards. Unfortunately, biomedical ontologies only provide ontological definitions that answer What is it? questions, but no method-dependent empirical recognition criteria that answer How does it look?

QUESTIONS

Consequently, biomedical ontologies contain knowledge of the underlying ontological nature of structural kinds, but often lack sufficient diagnostic knowledge to unambiguously determine the reference of a term.

RESULTS

We argue that this is because ontology terms are usually textually defined and conceived as essentialistic classes, while recognition criteria often require perception-based definitions because perception-based contents more efficiently document and communicate spatial and temporal information-a picture is worth a thousand words. Therefore, diagnostic knowledge often must be conceived as cluster classes or fuzzy sets. Using several examples from anatomy, we point out the importance of diagnostic knowledge in anatomical research and discuss the role of cluster classes and fuzzy sets as concepts of grouping needed in anatomy ontologies in addition to essentialistic classes. In this context, we evaluate the role of the biological type concept and discuss its function as a general container concept for groupings not covered by the essentialistic class concept.

CONCLUSIONS

We conclude that many recognition criteria can be conceptualized as text-based cluster classes that use terms that are in turn based on perception-based fuzzy set concepts. Finally, we point out that only if biomedical ontologies model also relevant diagnostic knowledge in addition to ontological knowledge, they will fully realize their potential and contribute even more substantially to the establishment of FAIR and eScience-compliant data and metadata standards in the life sciences.

Improving Taxonomic Practices and Enhancing Its Extensibility—An Example from Araneology

Planetary extinction of biodiversity underscores the need for taxonomy. Here, we scrutinize spider taxonomy over the last decade (2008–2018), compiling 2083 published accounts of newly described species. We evaluated what type of data were used to delineate species, whether data were made freely available, whether an explicit species hypothesis was stated, what types of media were used, the sample sizes, and the degree to which species constructs were integrative. The findings we report reveal that taxonomy remains largely descriptive, not integrative, and provides no explicit conceptual framework. Less than 4% of accounts explicitly stated a species concept and over one-third of all new species described were based on 1–2 specimens or only one sex. Only ~5% of studies made data freely available, and only ~14% of all newly described species employed more than one line of evidence, with molecular data used in ~6% of the studies. These same trends have been discovered in other animal groups, and therefore we find it logical that taxonomists face an uphill challenge when justifying the scientific rigor of their field and securing the needed resources. To move taxonomy forward, we make recommendations that, if implemented, will enhance its rigor, repeatability, and scientific standards.

FAIR data representation in times of eScience: a comparison of instance-based and class-based semantic representations of empirical data using phenotype descriptions as example

BACKGROUND

The size, velocity, and heterogeneity of Big Data outclasses conventional data management tools and requires data and metadata to be fully machine-actionable (i.e., eScience-compliant) and thus findable, accessible, interoperable, and reusable (FAIR). This can be achieved by using ontologies and through representing them as semantic graphs. Here, we discuss two different semantic graph approaches of representing empirical data and metadata in a knowledge graph, with phenotype descriptions as an example. Almost all phenotype descriptions are still being published as unstructured natural language texts, with far-reaching consequences for their FAIRness, substantially impeding their overall usability within the life sciences. However, with an increasing amount of anatomy ontologies becoming available and semantic applications emerging, a solution to this problem becomes available. Researchers are starting to document and communicate phenotype descriptions through the Web in the form of highly formalized and structured semantic graphs that use ontology terms and Uniform Resource Identifiers (URIs) to circumvent the problems connected with unstructured texts.

RESULTS

Using phenotype descriptions as an example, we compare and evaluate two basic representations of empirical data and their accompanying metadata in the form of semantic graphs: the class-based TBox semantic graph approach called Semantic Phenotype and the instance-based ABox semantic graph approach called Phenotype Knowledge Graph. Their main difference is that only the ABox approach allows for identifying every individual part and property mentioned in the description in a knowledge graph. This technical difference results in substantial practical consequences that significantly affect the overall usability of empirical data. The consequences affect findability, accessibility, and explorability of empirical data as well as their comparability, expandability, universal usability and reusability, and overall machine-actionability. Moreover, TBox semantic graphs often require querying under entailment regimes, which is computationally more complex.

CONCLUSIONS

We conclude that, from a conceptual point of view, the advantages of the instance-based ABox semantic graph approach outweigh its shortcomings and outweigh the advantages of the class-based TBox semantic graph approach. Therefore, we recommend the instance-based ABox approach as a FAIR approach for documenting and communicating empirical data and metadata in a knowledge graph.

Objectivity in rare disease research: A philosophical approach

Individuals living with rare conditions are faced with important challenges derived from the rarity of their conditions and aggravated by the low priority given to rare disease research. However, current realities of rare disease research require consideration of the relationship between subjectivity and 'traditional' objectivity. Objectivity in research has traditionally been associated with processes and descriptions that are independent of the investigator. The need for researchers to provide unbiased knowledge and achieve a balance between objectivity and the underlying values in nursing and scientific research requires an examination of how objectivity is conceptualized within the context of rare disease research. The aim of this paper is to examine scientific objectivity in rare disease research from a philosophical viewpoint and, in doing so, demonstrate the need to redefine it to reflect the current scientific environment. As such, healthcare providers working on this field need to redefine objectivity around ethical and moral obligation to advance science in an equitable manner with the end goal to produce knowledge that is trustworthy and beneficial to our patients.

The Spider Anatomy Ontology (SPD)—A Versatile Tool to Link Anatomy with Cross-Disciplinary Data

Spiders are a diverse group with a high eco-morphological diversity, which complicates anatomical descriptions especially with regard to its terminology. New terms are constantly proposed, and definitions and limits of anatomical concepts are regularly updated. Therefore, it is often challenging to find the correct terms, even for trained scientists, especially when the terminology has obstacles such as synonyms, disputed definitions, ambiguities, or homonyms. Here, we present the Spider Anatomy Ontology (SPD), which we developed combining the functionality of a glossary (a controlled defined vocabulary) with a network of formalized relations between terms that can be used to compute inferences. The SPD follows the guidelines of the Open Biomedical Ontologies and is available through the NCBO BioPortal (ver. 1.1). It constitutes of 757 valid terms and definitions, is rooted with the Common Anatomy Reference Ontology (CARO), and has cross references to other ontologies, especially of arthropods. The SPD offers a wealth of anatomical knowledge that can be used as a resource for any scientific study as, for example, to link images to phylogenetic datasets, compute structural complexity over phylogenies, and produce ancestral ontologies. By using a common reference in a standardized way, the SPD will help bridge diverse disciplines, such as genomics, taxonomy, systematics, evolution, ecology, and behavior.

Whole-genome duplication and hemoglobin differentiation traits between allopatric populations of Brazilian Odontophrynus americanus species complex (Amphibia, Anura)

Two allopatric populations of Brazilian diploid and tetraploid Odontophrynus americanus species complex, both from São Paulo state, had their blood hemoglobin biochemically analyzed. In addition, these specimens were cytogenetically characterized. Biochemical characterization of hemoglobin expression showed a distinct banding pattern between the allopatric specimens. Besides this, two distinct phenotypes, not linked to ploidy, sex, or age, were observed in adult animals of both populations. Phenotype A exhibits dark-colored body with small papillae, ogival-shaped jaw with reduced interpupillary distance and shorter hind limbs. Phenotype B shows yellowish-colored body with larger papillae, arch-shaped jaw with broader interpupillary distance and longer hind limbs. Intermediate phenotypes were also found. Considering the geographical isolation of both populations, differences in chromosomal secondary constrictions and distinct hemoglobins banding patterns, these data indicate that 2n and 4n populations represent cryptic species in the O. americanus species complex. The observed phenotypic diversity can be interpreted as population genetic variability. Eventually future data may indicate a probable beginning of speciation in these Brazilian frogs. Such inter- and intrapopulational differentiation/speciation process indicates that O. americanus species complex taxonomy deserves further evaluation by genomics and metabarcoding communities, also considering the pattern of hemoglobin expression, in South American frogs.

Organizing phenotypic data-a semantic data model for anatomy

BACKGROUND

Currently, almost all morphological data are published as unstructured free text descriptions. This not only brings about terminological problems regarding semantic transparency, which hampers their re-use by non-experts, but the data cannot be parsed by computers either, which in turn hampers their integration across many fields in the life sciences, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. With an ever-increasing amount of available ontologies and the development of adequate semantic technology, however, a solution to this problem becomes available. Instead of free text descriptions, morphological data can be recorded, stored, and communicated through the Web in the form of highly formalized and structured directed graphs (semantic graphs) that use ontology terms and URIs as terminology.

RESULTS

After introducing an instance-based approach of recording morphological descriptions as semantic graphs (i.e., Semantic Instance Anatomy Knowledge Graphs) and discussing accompanying metadata graphs, I propose a general scheme of how to efficiently organize the resulting graphs in a tuple store framework based on instances of defined named graph ontology classes. The use of such named graph resources allows meaningful fragmentation of the data, which in turn enables subsequent specification of all kinds of data views for managing and accessing morphological data.

CONCLUSIONS

Morphological data that comply with the here proposed semantic data model will not only be computer-parsable but also re-usable by non-experts and could be better integrated with other sources of data in the life sciences. This would allow morphology as a discipline to further participate in eScience and Big Data.

Levels and building blocks-toward a domain granularity framework for the life sciences

BACKGROUND

With the emergence of high-throughput technologies, Big Data and eScience, the use of online data repositories and the establishment of new data standards that require data to be computer-parsable become increasingly important. As a consequence, there is an increasing need for an integrated system of hierarchies of levels of different types of material entities that helps with organizing, structuring and integrating data from disparate sources to facilitate data exploration, data comparison and analysis. Theories of granularity provide such integrated systems.

RESULTS

On the basis of formal approaches to theories of granularity authored by information scientists and ontology researchers, I discuss the shortcomings of some applications of the concept of levels and argue that the general theory of granularity proposed by Keet circumvents these problems. I introduce the concept of building blocks, which gives rise to a hierarchy of levels that can be formally characterized by Keet's theory. This hierarchy functions as an organizational backbone for integrating various other hierarchies that I briefly discuss, resulting in a domain granularity framework for the life sciences. I also discuss the consequences of this granularity framework for the structure of the top-level category of 'material entity' in Basic Formal Ontology.

CONCLUSIONS

The domain granularity framework suggested here is meant to provide the basis on which a more comprehensive information framework for the life sciences can be developed, which would provide the much needed conceptual framework for representing domains that cover multiple granularity levels. This framework can be used for intuitively structuring data in the life sciences, facilitating data exploration, and it can be employed for reasoning over different granularity levels across different hierarchies. It would provide a methodological basis for establishing comparability between data sets and for quantitatively measuring their degree of semantic similarity.

SOCCOMAS: a FAIR web content management system that uses knowledge graphs and that is based on semantic programming

We introduce Semantic Ontology-Controlled application for web Content Management Systems (SOCCOMAS), a development framework for FAIR ('findable', 'accessible', 'interoperable', 'reusable') Semantic Web Content Management Systems (S-WCMSs). Each S-WCMS run by SOCCOMAS has its contents managed through a corresponding knowledge base that stores all data and metadata in the form of semantic knowledge graphs in a Jena tuple store. Automated procedures track provenance, user contributions and detailed change history. Each S-WCMS is accessible via both a graphical user interface (GUI), utilizing the JavaScript framework AngularJS, and a SPARQL endpoint. As a consequence, all data and metadata are maximally findable, accessible, interoperable and reusable and comply with the FAIR Guiding Principles. The source code of SOCCOMAS is written using the Semantic Programming Ontology (SPrO). SPrO consists of commands, attributes and variables, with which one can describe an S-WCMS. We used SPrO to describe all the features and workflows typically required by any S-WCMS and documented these descriptions in a SOCCOMAS source code ontology (SC-Basic). SC-Basic specifies a set of default features, such as provenance tracking and publication life cycle with versioning, which will be available in all S-WCMS run by SOCCOMAS. All features and workflows specific to a particular S-WCMS, however, must be described within an instance source code ontology (INST-SCO), defining, e.g. the function and composition of the GUI, with all its user interactions, the underlying data schemes and representations and all its workflow processes. The combination of descriptions in SC-Basic and a given INST-SCO specify the behavior of an S-WCMS. SOCCOMAS controls this S-WCMS through the Java-based middleware that accompanies SPrO, which functions as an interpreter. Because of the ontology-controlled design, SOCCOMAS allows easy customization with a minimum of technical programming background required, thereby seamlessly integrating conventional web page technologies with semantic web technologies. SOCCOMAS and the Java Interpreter are available from (https://github.com/SemanticProgramming).

Towards a semantic approach to numerical tree inference in phylogenetics

Conventional approaches to phylogeny reconstruction require a character analysis step prior to and methodologically separated from a numerical tree inference step. The former results in a character matrix that contains the empirical data analysed in the latter. This separation of steps involves various methodological and conceptual problems (e.g. homology assessment independent of tree inference and character optimization, character dependencies, discounting of alternative homology hypotheses). In morphology, the character analysis step covers the stages of morphological comparative studies, homology assessment and the identification and coding of morphological characters. Unfortunately, only the last stage requires some formalism, whereas the preceding stages are commonly regarded to be pre-rational and intuitive, which is why their reproducibility and analytical accessibility is limited. Here, I introduce a rational for a semantic approach to numerical tree inference that uses sets of semantic instance anatomies as data source instead of character matrices, thereby avoiding the above-mentioned problems. A semantic instance anatomy is an ontology-based description of the anatomical organization of a specimen in the form of a semantic graph. The semantic approach to numerical tree inference combines and integrates the steps of character analysis and numerical tree inference and makes both analytically accessible and communicable. Before outlining first steps for a research programme dedicated to the semantic approach to numerical tree inference, I discuss in detail the methodological, conceptual, and computational challenges and requirements that first have to be dealt with before adequate algorithms can be developed.

Entomological Collections in the Age of Big Data

With a million described species and more than half a billion preserved specimens, the large scale of insect collections is unequaled by those of any other group. Advances in genomics, collection digitization, and imaging have begun to more fully harness the power that such large data stores can provide. These new approaches and technologies have transformed how entomological collections are managed and utilized. While genomic research has fundamentally changed the way many specimens are collected and curated, advances in technology have shown promise for extracting sequence data from the vast holdings already in museums. Efforts to mainstream specimen digitization have taken root and have accelerated traditional taxonomic studies as well as distribution modeling and global change research. Emerging imaging technologies such as microcomputed tomography and confocal laser scanning microscopy are changing how morphology can be investigated. This review provides an overview of how the realization of big data has transformed our field and what may lie in store.

Data Sources for Trait Databases: Comparing the Phenomic Content of Monographs and Evolutionary Matrices

Databases of organismal traits that aggregate information from one or multiple sources can be leveraged for large-scale analyses in biology. Yet the differences among these data streams and how well they capture trait diversity have never been explored. We present the first analysis of the differences between phenotypes captured in free text of descriptive publications ('monographs') and those used in phylogenetic analyses ('matrices'). We focus our analysis on osteological phenotypes of the limbs of four extinct vertebrate taxa critical to our understanding of the fin-to-limb transition. We find that there is low overlap between the anatomical entities used in these two sources of phenotype data, indicating that phenotypes represented in matrices are not simply a subset of those found in monographic descriptions. Perhaps as expected, compared to characters found in matrices, phenotypes in monographs tend to emphasize descriptive and positional morphology, be somewhat more complex, and relate to fewer additional taxa. While based on a small set of focal taxa, these qualitative and quantitative data suggest that either source of phenotypes alone will result in incomplete knowledge of variation for a given taxon. As a broader community develops to use and expand databases characterizing organismal trait diversity, it is important to recognize the limitations of the data sources and develop strategies to more fully characterize variation both within species and across the tree of life.

High-precision morphology: bifocal 4D-microscopy enables the comparison of detailed cell lineages of two chordate species separated for more than 525 million years

BACKGROUND

Understanding the evolution of divergent developmental trajectories requires detailed comparisons of embryologies at appropriate levels. Cell lineages, the accurate visualization of cleavage patterns, tissue fate restrictions, and morphogenetic movements that occur during the development of individual embryos are currently available for few disparate animal taxa, encumbering evolutionarily meaningful comparisons. Tunicates, considered to be close relatives of vertebrates, are marine invertebrates whose fossil record dates back to 525 million years ago. Life-history strategies across this subphylum are radically different, and include biphasic ascidians with free swimming larvae and a sessile adult stage, and the holoplanktonic larvaceans. Despite considerable progress, notably on the molecular level, the exact extent of evolutionary conservation and innovation during embryology remain obscure.

RESULTS

Here, using the innovative technique of bifocal 4D-microscopy, we demonstrate exactly which characteristics in the cell lineages of the ascidian Phallusia mammillata and the larvacean Oikopleura dioica were conserved and which were altered during evolution. Our accurate cell lineage trees in combination with detailed three-dimensional representations clearly identify conserved correspondence in relative cell position, cell identity, and fate restriction in several lines from all prospective larval tissues. At the same time, we precisely pinpoint differences observable at all levels of development. These differences comprise fate restrictions, tissue types, complex morphogenetic movement patterns, numerous cases of heterochronous acceleration in the larvacean embryo, and differences in bilateral symmetry.

CONCLUSIONS

Our results demonstrate in extraordinary detail the multitude of developmental levels amenable to evolutionary innovation, including subtle changes in the timing of fate restrictions as well as dramatic alterations in complex morphogenetic movements. We anticipate that the precise spatial and temporal cell lineage data will moreover serve as a high-precision guide to devise experimental investigations of other levels, such as molecular interactions between cells or changes in gene expression underlying the documented structural evolutionary changes. Finally, the quantitative amount of digital high-precision morphological data will enable and necessitate software-based similarity assessments as the basis of homology hypotheses.

Finding our way through phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.

Folding wings like a cockroach: a review of transverse wing folding ensign wasps (Hymenoptera: Evaniidae: Afrevania and Trissevania)

We revise two relatively rare ensign wasp genera, whose species are restricted to Sub-Saharan Africa: Afrevania and Trissevania. Afrevania longipetiolata sp. nov., Trissevania heatherae sp. nov., T. hugoi sp. nov., T. mrimaensis sp. nov. and T. slideri sp. nov. are described, males and females of T. anemotis and Afrevania leroyi are redescribed, and an identification key for Trissevaniini is provided. We argue that Trissevania mrimaensis sp. nov. and T. heatherae sp. nov. populations are vulnerable, given their limited distributions and threats from mining activities in Kenya. We hypothesize that these taxa together comprise a monophyletic lineage, Trissevaniini, tr. nov., the members of which share the ability to fold their fore wings along two intersecting fold lines. Although wing folding of this type has been described for the hind wing of some insects four-plane wing folding of the fore wing has never been documented. The wing folding mechanism and the pattern of wing folds of Trissevaniini is shared only with some cockroach species (Blattodea). It is an interesting coincidence that all evaniids are predators of cockroach eggs. The major wing fold lines of Trissevaniini likely are not homologous to any known longitudinal anatomical structures on the wings of other Evaniidae. Members of the new tribe share the presence of a coupling mechanism between the fore wing and the mesosoma that is composed of a setal patch on the mesosoma and the retinaculum of the fore wing. While the setal patch is an evolutionary novelty, the retinaculum, which originally evolved to facilitate fore and hind wing coupling in Hymenoptera, exemplifies morphological exaptation. We also refine and clarify the Semantic Phenotype approach used in previous taxonomic revisions and explore the consequences of merging new with existing data. The way that semantic statements are formulated can evolve in parallel, alongside improvements to the ontologies themselves.