Web visualization dashboards are popular. We propose a system called RAIV that can capture and archive web visualizations into self-contained objects. RAIV also uses a client-server architecture to host and manage archived objects as online galleries, which users can use a standard web browser to experience without needing to install any additional software. RAIV supports intelligent search as well. When a search target has been found, RAIV can show the interaction path required to reach that target. We demonstrate RAIV’s capability using a genomics web visualization system called KnowEnG from NCSA and publicly available census data visualizations from US Census.
The rise in crime rates over the past few years is a major issue and is a huge source of worry for police departments and law enforcement organizations. Crime severely harms the lives of victims and the communities they live in many places throughout the world. It is an issue of public disturbance, and large cities often see criminal activity. Many studies, media, and websites include statistics on crime and it is contributing elements, such as population, unemployment, and poverty rate. This paper compares and visualizes the crime data for four different cities in the USA, namely Chicago, Baltimore, Dallas, and Denton. We assess areas that are significantly affected based on zip codes and variations in crime categories. As the crime rates have significantly changed both upward and downward throughout time, these changes are compared to their external causes such as population, unemployment, and poverty. The results show crime frequency and distribution across four different cities and supply valuable information about the complex relationship between social factors and criminal behavior. These results and outcomes will help the police department and law enforcement organizations better understand crime issues, map crime incidents onto a geographical map, and supply insight into factors affecting crime that will help them deploy resources and help in their decision-making process.