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XR4DRAMA Knowledge Graph: A Knowledge Graph for Disaster Management

Authors: Alexandros Vassiliades; Spyridon Symeonidis; Sotiris Diplaris; Georgios Tzanetis; Stefanos Vrochidis; Nick Bassiliades; Ioannis Kompatsiaris;

XR4DRAMA Knowledge Graph: A Knowledge Graph for Disaster Management

Abstract

The evolution of Knowledge Graphs (KGs), during the last two decades, has encouraged developers to create more and more context related KGs. This advance is extremely important because Artificial Intelligence (AI) applications can access open domain specific information in a semantically rich, machine understandable format. In this paper, we present the XR4DRAMA KG which can represent information for disaster management. More specifically, the XR4DRAMA KG can represent information about: (a) Observations and Events (e.g., data collection of biometric sensors, information in photos and text messages), (b) Spatio-temporal (e.g., highlighted locations and timestamps), (c) Mitigation and response plans in crisis (e.g., first responder teams). Moreover, we offer a mechanism that can create or update Points-Of-Interest (POIs), based on a visual or textual messages received from users.

Keywords

Points of Interest, Knowledge Graphs, POI Management Mechanism, Disaster Management

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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4
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35
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