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              <classCode scheme="vocinrae-old" n="animal d'élevage">animal d'élevage</classCode>
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              <classCode scheme="vocinrae-old" n="production d'embryon">production d'embryon</classCode>
              <classCode scheme="vocinrae-old" n="système d'élevage">système d'élevage</classCode>
              <classCode scheme="vocinrae-old" n="développement de l'embryon">développement de l'embryon</classCode>
              <classCode scheme="vocinrae-old" n="trait phénotypique">trait phénotypique</classCode>
              <classCode scheme="vocinrae-old" n="condition d'élevage">condition d'élevage</classCode>
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              <p>The development and the use of ontologies contribute to a better organization and use of the huge amount of knowledge available in biology, but could even contribute better when used worldwide to share common bases when publishing morphological data or molecular phenotypes (Gene Ontology, for example). We have built ATOL (http://www.atol-ontology.com) for Änimal Trait Ontology for Livestock\" that is devoted to the definition and organization of phenotypic traits of farm animals including fish, birds and mammals. Given that phenotypes result from the action of both the genotype and the environment, a precise description of the animal rearing environments is critical. We thus created EOL for Ënvironment Ontology for Livestock\", to describe the livestock systems and the rearing conditions in a generic manner. We could however extend that for in vitro and in vivo produced embryos to define the culture media, the origins of the gametes or the statuses of the dams that carry the embryos (breed, parity, energy balance, farming conditions). The combination of embryonic traits (in ATOL) and rearing conditions (in EOL) would enable a standardized and precise annotation of phenotypic databases linked to explicit metadata. Such ontologies also appear critical resources for automated semantic analyses that retrieve accurate information from relevant scientific or technical documents. Moreover, integrative and systemic approaches based on modelling would gain from a formal representation of knowledge that could then be automatically processed. The context and the content of both ontologies, as well as their putative application to embryo production and development, will be presented.</p>
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