Ontology Creation and Management Tools: the Case of Anatomical Connectivity

Ontologies are essential for developing standardized vocabularies and defining relationships that help describe and interpret data from diverse sources. They are crucial for achieving semantic interoperability in many domains, allowing different systems to exchange data with a consistent and shared meaning. Ontologies are extensively used in biological and biomedical research Hoehndorf et al. (2015); Antezana et al. (2009), due to their ability to: provide standard identifiers for classes and relationships representing complex phenomena; include metadata to clarify the intended meaning of classes and relationships; include machine-readable definitions that allow computational access to class properties and relationships; standardize vocabulary across multiple data sources. Ontology-based data integration plays a vital role in neuroscience, where researchers synthesize knowledge across physiology, anatomy, molecular and developmental biology, cytology, and mathematical modeling to support accurate data representation, analysis, and simulation. A common challenge for many large neuroscience projects is the integration of data across a wide diversity of species, spatial resolutions, and temporal scales.