Abstract The spectacular radiation of insects has produced a stunning diversity of phenotypes. During the past 250 years, research on insect systematics has generated hundreds of terms for naming and comparing them. In its current form, this terminological diversity is presented in natural language and lacks formalization, which prohibits computer-assisted comparison using semantic web technologies. Here we propose a Model for Describing Cuticular Anatomical Structures (MoDCAS) which incorporates structural properties and positional relationships for standardized, consistent, and reproducible descriptions of arthropod phenotypes. We applied the MoDCAS framework in creating the ontology for the Anatomy of the Insect Skeleto-Muscular system (AISM). The AISM is the first general insect ontology that aims to cover all taxa by providing generalized, fully logical, and queryable, definitions for each term. It was built using the Ontology Development Kit (ODK), which maximizes interoperability with Uberon (Uberon multi-species anatomy ontology) and other basic ontologies, enhancing the integration of insect anatomy into the broader biological sciences. A template system for adding new terms, extending, and linking the AISM to additional anatomical, phenotypic, genetic, and chemical ontologies is also introduced. The AISM is proposed as the backbone for taxon-specific insect ontologies and has potential applications spanning systematic biology and biodiversity informatics, allowing users to (1) use controlled vocabularies and create semi-automated computer-parsable insect morphological descriptions; (2) integrate insect morphology into broader fields of research, including ontology-informed phylogenetic methods, logical homology hypothesis testing, evo-devo studies, and genotype to phenotype mapping; and (3) automate the extraction of morphological data from the literature, enabling the generation of large-scale phenomic data, by facilitating the production and testing of informatic tools able to extract, link, annotate, and process morphological data. This descriptive model and its ontological applications will allow for clear and semantically interoperable integration of arthropod phenotypes in biodiversity studies.
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Semantic Localization for IoT
Euclidean geometry and Newtonian time with floating point numbers are
common computational models of the physical world. However, to achieve the kind
of cyber-physical collaboration that arises in the IoT, such a literal representation of
space and time may not be the best choice. In this chapter we survey location models
from robotics, the internet, cyber-physical systems, and philosophy. The diversity in
these models is justified by differing application demands and conceptualizations of
space (spatial ontologies). To facilitate interoperability of spatial knowledge across
representations,we propose a logical frameworkwherein a spatial ontology is defined
as a model-theoretic structure. The logic language induced from a collection of such
structures may be used to formally describe location in the IoT via semantic localization.
Space-aware IoT services gain advantages for privacy and interoperability
when they are designed for the most abstract spatial-ontologies as possible.We finish
the chapter with definitions for open ontologies and logical inference.
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- Award ID(s):
- 1836601
- NSF-PAR ID:
- 10311565
- Editor(s):
- Pandey, R.
- Date Published:
- Journal Name:
- Semantic IoT: Theory and Applications, Studies in Computational Intelligence 941
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1007/978-3-030-64619-6_16
