Geovisual Analytics and Interactive Machine Learning for Situational Awareness
It addresses the need for improved situational awareness for first responders during crises, but it appears incremental as it builds on existing visual analytics and interactive machine learning concepts.
The paper tackles the problem of providing first responders with real-time situational awareness by developing the Social Media Analytics Reporting Toolkit (SMART), a visual analytics platform that integrates social media data, resulting in successful adoption by many first responders.
The first responder community has traditionally relied on calls from the public, officially-provided geographic information and maps for coordinating actions on the ground. The ubiquity of social media platforms created an opportunity for near real-time sensing of the situation (e.g. unfolding weather events or crises) through volunteered geographic information. In this article, we provide an overview of the design process and features of the Social Media Analytics Reporting Toolkit (SMART), a visual analytics platform developed at Purdue University for providing first responders with real-time situational awareness. We attribute its successful adoption by many first responders to its user-centered design, interactive (geo)visualizations and interactive machine learning, giving users control over analysis.