Visualization and analytics tools for infectious disease epidemiology: a systematic review.

Background: A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) identify public health user needs and preferences for infectious disease information visualization tools; (2) identify existing infectious disease information visualization tools and characterize their architecture and features; (3) identify commonalities among approaches applied to different data types; and (4) describe tool usability evaluation efforts and barriers to the adoption of such tools.

Differences among cell-structure ontologies: FMA, GO, & CCO.

When different groups create models or ontologies of the same knowledge domain, this creates challenges for knowledge sharing. To identify these challenges, we compare cellular structure as modeled by the Foundational Model of Anatomy(FMA), the Gene Ontology (GO), and the Cell Component Ontology (CCO). These ontologies all model the physical anatomy of a cell, and we expected them to be similar in scope.