VACCINATED — Visual analytics for characterizing a pandemic spread VAST 2010 Mini Challenge 2 award: Support for future detection

Malik, Abish; Afzal, Shehzad; Hodgess, Erin M.; Ebert, David S.; Maciejewski, Ross

doi:10.1109/vast.2010.5652661

Cited by 1 publication

(1 citation statement)

References 3 publications

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“…We further note that the time series display is interactive, allowing users to touch the screen to get the incident count at any particular time. A time series tape measure tool [24] in the graph view allows users to determine the temporal distance between any two points on the graph. We also provide users with tools that allow them to accurately model the data using an Exponentially Weighted Moving Average (EWMA) control chart for event prediction [24].…”

Section: Time Series Viewmentioning

confidence: 99%

A Mobile Visual Analytics Approach for Law Enforcement Situation Awareness

Razip

Malik

Afzal

et al. 2014

2014 IEEE Pacific Visualization Symposium

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(a) Risk profile tools give time-and location-aware assessment of public safety using law enforcement data.(b) The mobile system can be used anywhere with cellular network coverage to visualize and analyze law enforcement data. Here, the system is being used as the user walks down a street. Abstract-The advent of modern smartphones and handheld devices has given analysts, decision-makers, and even the general public the ability to rapidly ingest data and translate it into actionable information on-the-go. In this paper, we explore the design and use of a mobile visual analytics toolkit for public safety data that equips law enforcement agencies and citizens with effective situation awareness and risk assessment tools. Our system provides users with a suite of interactive tools that allow them to perform analysis and detect trends, patterns and anomalies among criminal, traffic and civil (CTC) incidents. The system also provides interactive risk assessment tools that allow users to identify regions of potential high risk and determine the risk at any user-specfied location and time. Our system has been designed for the iPhone/iPad environment and is currently being used and evaluated by a consortium of law enforcement agencies. We report their use of the system and some initial feedback.

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Section: Time Series Viewmentioning

confidence: 99%