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The tissue microarray OWL schema: An open-source tool for sharing tissue microarray data

BACKGROUND: Tissue microarrays (TMAs) are enormously useful tools for translational research, but incompatibilities in database systems between various researchers and institutions prevent the efficient sharing of data that could help realize their full potential. Resource Description Framework (RDF...

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Detalles Bibliográficos
Autores principales: Kang, Hyunseok P., Borromeo, Charles D., Berman, Jules J., Becich, Michael J.
Formato: Texto
Lenguaje:English
Publicado: Medknow Publications 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2929536/
https://www.ncbi.nlm.nih.gov/pubmed/20805954
http://dx.doi.org/10.4103/2153-3539.65347
Descripción
Sumario:BACKGROUND: Tissue microarrays (TMAs) are enormously useful tools for translational research, but incompatibilities in database systems between various researchers and institutions prevent the efficient sharing of data that could help realize their full potential. Resource Description Framework (RDF) provides a flexible method to represent knowledge in triples, which take the form Subject-Predicate-Object. All data resources are described using Uniform Resource Identifiers (URIs), which are global in scope. We present an OWL (Web Ontology Language) schema that expands upon the TMA data exchange specification to address this issue and assist in data sharing and integration. METHODS: A minimal OWL schema was designed containing only concepts specific to TMA experiments. More general data elements were incorporated from predefined ontologies such as the NCI thesaurus. URIs were assigned using the Linked Data format. RESULTS: We present examples of files utilizing the schema and conversion of XML data (similar to the TMA DES) to OWL. CONCLUSION: By utilizing predefined ontologies and global unique identifiers, this OWL schema provides a solution to the limitations of XML, which represents concepts defined in a localized setting. This will help increase the utilization of tissue resources, facilitating collaborative translational research efforts.