GeoGraphVis: A Knowledge Graph and Geovisualization Empowered Cyberinfrastructure to Support Disaster Response and Humanitarian Aid

TLDR

Disasters are increasingly frequent and intense, and timely response requires rapid assembly and visualization of real‑time, multi‑source geospatial data to build situational awareness. This paper presents GeoGraphVis, a cyberinfrastructure that uses knowledge‑graph technology and advanced visualization to support intelligent decision making in disaster response. GeoGraphVis constructs a location‑aware knowledge graph linking cross‑domain data, models expert workflows as machine‑understandable decision paths, and provides scene‑based interactive visual analytics to guide humanitarian action.

Abstract

The past decade has witnessed an increasing frequency and intensity of disasters, from extreme weather, drought, and wildfires to hurricanes, floods, and wars. Providing timely disaster response and humanitarian aid to these events is a critical topic for decision makers and relief experts in order to mitigate impacts and save lives. When a disaster occurs, it is important to acquire first-hand, real-time information about the potentially affected area, its infrastructure, and its people in order to develop situational awareness and plan a response to address the health needs of the affected population. This requires rapid assembly of multi-source geospatial data that need to be organized and visualized in a way to support disaster-relief efforts. In this paper, we introduce a new cyberinfrastructure solution—GeoGraphVis—that is empowered by knowledge graph technology and advanced visualization to enable intelligent decision making and problem solving. There are three innovative features of this solution. First, a location-aware knowledge graph is created to link and integrate cross-domain data to make the graph analytics-ready. Second, expert-driven disaster response workflows are analyzed and modeled as machine-understandable decision paths to guide knowledge exploration via the graph. Third, a scene-based visualization strategy is developed to enable interactive and heuristic visual analytics to better comprehend disaster impact situations and develop action plans for humanitarian aid.