General Visualization Abstraction Algorithm for Geographic Map-based Directable Interfaces

Abstract

Emergency incident response, including Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) a.k.a. weapons of mass destruction incidents, is evolving from a response involving humans with equipment to a response system combining humans and thinking machines (e.g. robots). The robots, along with possibly other deployed sensors, will generate and capture volumes of information that will be presented in directable visualizations. This paper presents a novel approach to performing information abstraction (i.e., selection and grouping) and determining how each information item should be presented (i.e., its shape) in directable visualizations. This new approach employs the General Visualization Abstraction (GVA) algorithm to make salient and direct attention to the most relevant information items by determining an importance value for each information item based on the item's relationship with two classes of information: historically relevant and currently relevant information, and novel and emerging information.