Toolkit Designed To Make Biomedical Data Exploration Easier

Researchers have developed an open-source platform for creating software applications that make complex data understandable and accessible to those without sophisticated informatics expertise.

Commercial analytics tools tend to require biomedical researchers to understand underlying data models before being able to effectively explore and use large data sets, according to an article at the Journal of the American Informatics Association.

Researchers at the Children's Hospital of Philadelphia and Perelman School of Medicine at the University of Pennsylvania have validated the platform, called Harvest, on two test cases: pediatric cardiology diagnostic and procedure data, and infectious disease data published by the OpenMRS open-source electronic health record (EHR) project.

This platform helps researchers perform queries on individual or multiple attributes in disparate data types--vital signs, blood cell counts, lengthy DNA sequences, bar graphs--and export raw data in an analysis-ready format, according to an announcement.