Development of an ontology of animals in context within the OBO Foundry framework from a SNOMED-CT extension and subset

• Main Author: Santamaria, Suzanne Lamar
• Other Authors: Veterinary Medical Sciences
• Format: Others
• Published: Virginia Tech 2014
• Subjects: veterinary informatics; animals in context; biomedical ontologies; OBO; SNOMED-CT
• Online Access: http://hdl.handle.net/10919/32400; http://scholar.lib.vt.edu/theses/available/etd-05082012-121749/

Animal classification needs vary by use and application. The Linnaean taxonomy is an important animal classification scheme but does not portray key animal identifying information like sex, age group, physiologic stage, living environment and role in production systems such as farms. Ontologies are created and used for defining, organizing and classifying information in a domain to enable learning and sharing of information. This work develops an ontology of animal classes that form the basis for communication of animal identifying information among animal managers, medical professionals caring for animals and biomedical researchers involved in disciplines as diverse as wildlife ecology and dairy science. The Animals in Context Ontology (ACO) was created from an extension and subset of the Systematized Nomenclature of Medicine â Clinical Terms (SNOMED-CT). The principles of the Open Biological and Biomedical Ontologies (OBO) Foundry were followed and freely available tools were used. ACO includes normal development and physiologic animal classes as well animal classes where humans have assigned the animalâ s role. ACO is interoperable with and includes classes from other OBO Foundry ontologies such as the Gene Ontology (GO). Meeting many of the OBO Foundry principles was straightforward but difficulties were encountered with missing and problematic content in some of the OBO ontologies. Additions and corrections were submitted to four ontologies. Some information in ACO could not be represented formally because of inconsistency in husbandry practices. ACO classes are of interest to science, medicine and agriculture, and can connect information between animal and human systems to enable knowledge discovery. === Master of Science