A. Vassiliades, S. Symeonidis, S. Diplaris, G. Tzanetis, S. Vrochidis, N. Bassiliades, I. Kompatsiaris, “XR4DRAMA Knowledge Graph: A Knowledge Graph for Disaster Management”, Proc. 17th IEEE International Conference on Semantic Computing (ICSC-2023), 1-3 Feb 2023, Laguna Hills, California, USA, Hybrid event, pp. 262-265.

Author(s): A. Vassiliades, S. Symeonidis, S. Diplaris, G. Tzanetis, S. Vrochidis, N. Bassiliades, I. Kompatsiaris

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Appeared In: Proc. 17th IEEE International Conference on Semantic Computing (ICSC-2023), 1-3 Feb 2023, Laguna Hills, California, USA, Hybrid event, pp. 262-265.

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

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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.