In the area of crisis and disaster management there is a rising need for a smart way to select and filter relevant data. So far a lot of research has been conducted dealing with the cooperation of different organizations, their communication, emergency plans, sensor architectures, etc. However, the structure of data and the incompatibilities in their interpretation remain open issues. Recent developments in the areas of Semantic Sensor Web systems, Semantic Time Series Processing, Ontology Mapping, and Reasoning can yield substantial benefits when successfully applied in crisis and disaster management scenarios.
The area of environmental monitoring, especially regarding climate change, environmental protection and sustainability is closely related. They can be understood as the starting scenario for crisis and disaster management and therefore provide a broad sandbox for the development of supportive ontologies and integration of Semantic Web technologies in order to prevent situations that cause a negative impact to the environment before, during, and after a disaster. A plethora of independently run platforms store data and information about climate change and environmental issues, however little are connected to provide the possibility to generate an added value.
This workshop shall spark an interdisciplinary cooperation between these topics and establish synergies with existing Semantic Web approaches and technologies. Semantic Web technologies appear to show a very good fit to current problems in Crisis and Disaster Management and Environmental Monitoring and decision making.
We encourage the submission of papers describing ideas, technologies, and projects promoting the development, validation and modeling of ontologies for crisis and disaster management and environmental protection, reasoning in decision support systems, smart or semantic sensors, semantically enriched time series, and related subjects.
The main focus of this session is to present, discuss and showcase the possibilities how both fields can benefit from Semantic Web technologies and semantically-enriched environmental monitoring techniques.