Modeling neuroanatomical experimental design using the Ontology of Experimental Variables and Values (OoEVV)
Gully A.P.C. Burns (Information Sciences Institute / University of Southern California), Marcelo Tallis (Information Sciences Institute / University of Southern California), Jessica Turner (Mind Research Network / University of New Mexico)
The Knowledge Engineering from Experimental Design (KEfED) approach provides a tool-driven methodology for describing experimental observations based on dependency relationships between variables. We here describe ‘the Ontology of Experimental Variables and Values’ (OoEVV), a modular ‘Ontology Design Pattern’ (ODP) to provide a reusable set of components that enable the curation of terminologies for use within KEfED models that may be linked to formal ontological definitions where required. This system provides an ontology curation methodology for all semantic components of the KEfED modeling approach (including entities, processes and variables used in the experimental protocol). We present a particular type of variable for representing neuroanatomical data spatially. These variables can be used to describe injection sites, tracer labeling locations, or gene expression regions. We make available alternative metrics to express neuroanatomical locations for curators to choose the one that better fits their needs. For example, we provide one metric for describing locations qualitatively in relation to atlas based neuroanatomical subdivisions while we also provide another metric for describing locations quantitatively in relation to a stereotactic coordinate system. In any case, the referenced spatial framework is explicitly represented enabling bioinformatics systems to implement some means for comparing data expressed in different metric systems.
Although the system is designed to offer the smallest possible ontological commitment for any given experimental variable, we provide a mechanism to link OoEVV elements to other ontologies. Finally, the system is consistent with ontological best practices in terms of providing good definitions and documentation, reuse of terminology wherever possible and compatibility with existing ontology formats and standards. We provide a practical curation toolset that may be used by domain experts to develop a structured lightweight terminology that may be accessed via the NCBO’s Bioportal.
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