The purpose of the national FaceBase consortium is to systemically acquire and integrate multiple forms of data in order to facilitate a systems level understanding of the causes and possible treatments for craniofacial abnormalities. A basic component of any such data integration effort is a controlled set of terms or keywords that can be associated with the data through data annotation, so that diverse data can be related via common terms. If in addition, the terms are related to each other in an ontology, then integration can occur at the level of meaning rather than simply via keywords. As part of FaceBase1 we designed and partially implemented the Ontology of Craniofacial Development and Malformation (OCDM), based on our Foundational Model of Anatomy ontology (FMA). The OCDM currently consists of components for representing human and mouse adult and developmental anatomy and malformations, as well as mappings between homologous structures in the two organisms. Since the focus of FaceBase1 was cleft lip and palate the initial focus of the ontology was representation of structures and developmental relations relevant to these conditions in mouse and human. In our proposed work we will greatly extend the OCDM to accommodate conditions of interest to FaceBase2 researchers, such as human and mouse facial, palatal, and cranial vault development, and dysmorphology such as craniosynostosis, midface hypoplasia, frontonasal dysplasia, craniofacial microsomia and microtia. These malformations will require extensive structural and developmental representation of the entire musculoskeletal system of the head, as well as associated soft tissue anatomy that includes the integumentary system, deep fascial system, viscerocranial mucosa, adipose tissue, eyes, ears, tongue, vasculature and neural network. In addition we will incorporate and add relations to the Zfin ontology to reflect the inclusion of zebrafish in FaceBase2. Versions of the OCDM will be released to the FaceBase Hub in OWL 2. By conforming to ontology best practices such as OWL 2 the OCDM will be interoperable with other efforts that are contributing to the overall world wide semantic web of linked data and knowledge.
Craniofacial abnormalities occur in over half of all congenital malformations. To understand the genetic and therefore causative basis for these disorders requires precise yet detailed integration of phenotypic and genotypic data from multiple sources. The ontology, data integration, data visualization and data exploration tools we will develop in the proposed research will greatly facilitate this integration by providing an underlying infrastructure for integration, together with a web-based graphical interface that allows craniofacial educators, clinicians and researchers to explore the integrated data within a context that is very familiar to them, namely 3-D anatomy.