Abstract
Biomedical researchers share a common challenge of making complex data understandable and accessible as they seek inherent relationships between attributes in disparate data types. Data discovery in this context is limited by a lack of query systems that efficiently show relationships between individual variables, but without the need to navigate underlying data models. We have addressed this need by developing Harvest, an opensource framework of modular components, and using it for the rapid development and deployment of custom data discovery software applications. Harvest incorporates visualizations of highly dimensional data in a web-based interface that promotes rapid exploration and export of any type of biomedical information, without exposing researchers to underlying data models. We evaluated Harvest with two cases: clinical data from pediatric cardiology and demonstration data from the OpenMRS project. Harvest's architecture and public open-source code offer a set of rapid application development tools to build data discovery applications for domain-specific biomedical data repositories. All resources, including the OpenMRS demonstration, can be found at http://harvest.research.chop.edu.
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CITATION STYLE
Pennington, J. W., Ruth, B., Italia, M. J., Miller, J., Wrazien, S., Loutrel, J. G., … White, P. S. (2014). Harvest: An open platform for developing web-based biomedical data discovery and reporting applications. Journal of the American Medical Informatics Association, 21(2), 379–383. https://doi.org/10.1136/amiajnl-2013-001825
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