| Resumo: |
Research databases, clinical systems, and lab systems all have different standards, formats and drivers for data capture, operation, analysis and integration. For interdisciplinary nutritional researchers, however, there is a dependence on all of these areas and technologies. While building and integrating these systems can be difficult, using agile practices including short iterations, testing and continuous integration methods, and close engagement with all stakeholders to create useful systems for translational research. Interoperability also requires good data standards, including the use of structured data dictionaries and existing data standards such as HL7, UMLS, LOINC, ICD, and OBO foundry ontologies.
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