BioPortal: Sharing and Analyzing Infectious Disease Information

Abstract

Infectious disease informatics (IDI) is an emerging field of study that systematically examines information management and analysis issues related to infectious disease prevention, detection, and management. IDI research is inherently interdisciplinary, drawing expertise from a number of fields including but not limited to various branches of information technologies such as data integration, data security, GIS, digital library, data mining and visualization, and other fields such as biostatistics and bioinformatics. Funded by the NSF through its Digital Government and Information Technology Research programs with support from the Intelligence Technology Innovation Center, we have been developing scalable technologies and related standards and protocols, implemented in the BioPortal system, to deal with various data sharing and analysis challenges arising in the field of IDI. BioPortal provides distributed, cross-jurisdictional access to datasets concerning several major infectious diseases (of both humans and animals) West Nile Virus (WNV), Botulism, Foot-and-Mouth Disease (FMD), and Chronic Wasting Disease (CWD). It also provides access to test data collected from the BioWatch system, an air pathogen sensing system developed to detect airborne hazards. In addition to data access, BioPortal provides advanced spatial-temporal data visualization and analysis capabilities, which are critically needed for infectious disease outbreak detection and can provide valuable information to facilitate disease outbreak management and response. The intended users of BioPortal include public health researchers and practitioners at all levels of the government including international partners, analysts and policy makers; the general public and students in public health or related fields; and law enforcement and national security personnel involved in counter bioterrorism efforts and emergency preparedness and response.

Reported research has been supported in part by the NSF through Digital Government Grant #EIA-9983304 and Information Technology Research Grant #IIS-0428241.