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

Wenwen Li*, Sizhe Wang, Xiao Chen, Yuanyuan Tian, Zhining Gu, Anna Lopez-Carr, Andrew Schroeder, Kitty Currier, Mark Schildhauer, Rui Zhu

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

25 Citations (Scopus)

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.

Original languageEnglish
Article number112
JournalISPRS International Journal of Geo-Information
Volume12
Issue number3
DOIs
Publication statusPublished - Mar 2023

Bibliographical note

Funding Information:
This work is in part supported by the National Science Foundation under award number 2033521.

Publisher Copyright:
© 2023 by the authors.

Keywords

  • big data
  • cyberinfrastructure
  • disaster response
  • humanitarian aid
  • knowledge graph
  • semantics
  • spatial decision support
  • storytelling
  • visual analytics
  • visualization

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