In the discipline of comparative morphology 
, phenotypic diversity is described in free text in a variety of ways, including detailed anatomical studies, descriptions of new species, and characters used in phylogenetic analyses. However, it is often difficult to compare phenotypes across taxa because of the different terminologies used in these descriptions. Researchers studying different anatomical regions, different taxa, or working within different biological specialties often have dissimilar terminologies 
. Furthermore, even when the same term is used, identifying publications that analyze the same structure is not trivial, and combining character matrices across studies is an even larger hurdle 
. If phenotypic diversity were represented in a common and computable manner, one would be better able to explore the wealth of data available across a broad range of anatomy, development, and taxa and also to relate this information to different domains of biological knowledge such as genomics, comparative embryology, and functional morphology 
. By grappling with phenotypic diversity in a structured and formal way, novel inquiries can be made across organismal phenotypic diversity, including evolved natural phenotypes and the mutant phenotypes of model systems.
This synthesis and discovery can be made feasible through the use of shared ontologies 
. An ontology is a structured, controlled vocabulary in which the terms and the relationships between the terms are defined using formal logic. It represents the knowledge of a discipline in a format that can be understood both by humans and by machines for computational inference. Ontology-based searches differ from keyword and text searches because they allow one to retrieve groups of related terms rather than only direct text matches of search terms. The reason for improved retrieval is that one can exploit the logical definitions 
and relations across terms and thereby infer additional information. Using an anatomy ontology with logical links to development and a database of ontology-based annotations to multiple species, for example, one might search for ‘intramembranous ossification’ and return frog ‘frontoparietal bone’ because it develops using this mode of ossification. One would also return chick ‘tibia’, an endochondral bone, because it also undergoes intramembranous ossification along the midshaft 
. Furthermore, even the simple use of synonyms facilitates retrieval; for example, a user searching on ‘skull’ would retrieve data tagged with ‘cranium’. Thus, an ontology can support grouping and comparison of data in significant ways by leveraging the logical relationships among concepts.
Ontologies can be used for standardizing terminology within disciplines and for clarifying and improving communication across domains. Most importantly, ontologies can be used to bring together disparate data in a logically consistent manner. Many anatomy ontologies are restricted to model organisms and are used for annotating gene expression and resulting phenotypes: for example if sonic hedgehog a
is not expressed in the neural tube of the zebrafish, the anterior neural tube is malformed 
. Recently, the evolutionary biology community has also begun to use anatomy ontologies because they provide a structured representation for comparative morphology and the potential to link comparative morphological data to the wealth of genomic, anatomical, and phenotype data available in model organism databases 
. However, model organism and taxon-specific anatomy ontologies have been largely developed semi-independently within their specific communities. As a result, the terminological subclass hierarchies of anatomical parts developed by different communities are frequently divergent. This poses significant obstacles to integrating data across species or projects. The resulting confusion can be remedied by consensus among workers from different disciplines, such as by bringing representatives from various domains together to agree on at least a common upper-level ontology, or by developing a bridging ontology that can be used for reasoning 
Motivated by comparative research questions that require reasoning across the taxonomic and phenotypic diversity of vertebrate skeletal morphologies at different biological scales, we sought a higher-level representation of skeletal anatomy that reconciles currently existing species-specific and multispecies ontological representations of the skeletal system (). To this end, we, a group of anatomy experts and ontologists, worked together to develop a module of high-level anatomy ontology concepts that unify more specific terms for the skeletal system. This module, which we call the Vertebrate Skeletal Anatomy Ontology (VSAO), integrates terms for cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages), and subdivisions of the skeletal system, thus enabling novel queries and computation across different levels of granularity and taxa. The upper-level skeletal terms in the VSAO can easily integrate terms for more specific structures and tissue types, including structures found in taxa that are not currently covered by existing anatomy ontologies. For example, placoderms, a group of extinct fossil fishes, possess a ‘scapular complex’, a cluster of dermal bones represented in VSAO as a type of ‘skeletal subdivision’ that is part of the pectoral girdle 
Vertebrate anatomy ontologies and others formally related to VSAO (*applicable to multiple species).
Rather than representing one strict classification of skeletal anatomy, the goal of developing these concepts was to accommodate the breadth of ways that biologists classify skeletal entities. The VSAO set of high-level skeletal system concepts will be a valuable resource to the fields of comparative morphology, development and genetics because of its integrative goal to unify existing vertebrate ontologies, thus enabling queries of disparate data sets across taxa, experimental studies, phylogenetic analyses, and genomics.