ARTÍCULO
TITULO

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 and Rui Zhu    

Resumen

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.

 Artículos similares

       
 
Xiu Li, Aron Henriksson, Martin Duneld, Jalal Nouri and Yongchao Wu    
Educational content recommendation is a cornerstone of AI-enhanced learning. In particular, to facilitate navigating the diverse learning resources available on learning platforms, methods are needed for automatically linking learning materials, e.g., in... ver más
Revista: Future Internet

 
Jun Li, Chenyang Zhang, Jianyi Zhang and Yanhua Shao    
To address the challenge of balancing privacy protection with regulatory oversight in blockchain transactions, we propose a regulatable privacy protection scheme for blockchain transactions. Our scheme utilizes probabilistic public-key encryption to obsc... ver más
Revista: Future Internet

 
Yong Yu, Shudong Chen, Rong Du, Da Tong, Hao Xu and Shuai Chen    
Temporal knowledge graphs play an increasingly prominent role in scenarios such as social networks, finance, and smart cities. As such, research on temporal knowledge graphs continues to deepen. In particular, research on temporal knowledge graph reasoni... ver más
Revista: Future Internet

 
Stefano Ferilli, Eleonora Bernasconi, Davide Di Pierro and Domenico Redavid    
With the progressive improvements in the power, effectiveness, and reliability of AI solutions, more and more critical human problems are being handled by automated AI-based tools and systems. For more complex or particularly critical applications, the l... ver más
Revista: Future Internet

 
Franco Bagnoli and Guido de Bonfioli Cavalcabo?    
We illustrate a simple model of knowledge scaffolding, based on the process of building a corpus of knowledge, each item of which is linked to ?previous? ones. The basic idea is that the relationships among the items of corpus can be essentially drawn as... ver más
Revista: Future Internet