Abstract: There is considerable interest in advance technologies to support crisis and disaster management as they face the challenges of designing, building, and maintaining large-scale distributed systems able to adapt to the dynamics and complexity of crises. Candidate technologies include Service Oriented Architecture (SOA), related Semantic Web technology, agent-based architecture and cognitive architectures. Each embodies some principles of the Adaptive Architecture-including modularity, openness, standards-based development, runtime support and importantly explicitness. However, truly adaptive architectures for crisis management will require some deepening the knowledge architecture's content and not just its representation. Light and more robust ontological models of situations are discussed to show how better formalization of conceptual patterns like “participation” can be developed to support cognitive architectures. The feasibility of an ontological design pattern approach is described as an avenue for future research and development describing specific types of situations.

Abstract: Fast and effective disaster management requires access to a multitude of heterogeneous, distributed, and quickly changing data sets, such as maps, satellite images, or governmental databases. In the last years, also the information created by affected persons on web sites such as flickr.com or blogger.com became an important and very quickly adapting source of information. We developed HUODINI, a prototype system for the flexible integration and visu-alization of heterogeneous data sources for disaster management. HUODINI is based on Semantic Web technologies, and in particular RDF, to offer maximal flexibility in the types of data sources it can integrate. It supports a hybrid push/pull approach to cater for the requirements of fast-changing sources, such as news feeds, and maximum performance for querying the integrated data set. In this paper, we describe the design goals underlying our approach, its architecture, and report on first experiences with the system.

Abstract: When carrying out tasks, police officers need up-to-date information contextualized to their current situation to support them in decision making. The results of a previous user study with the aim of capturing the information requirements of police officers have led to the implementation of a rule-based system for contextualized information delivery. In this paper, we present the overall system and discuss how the various sources of information are modelled using ontologies. Our focus is on the formalism for expressing the rules and the engine executing those rules to decide which information is relevant for specific users. These declarative rules can be modified independently of the code executing them, thus providing a principled way to adapt the system to new domains. Quantitative evaluations on scenarios constructed in cooperation with police officers show that precision and recall levels of our system are satisfactory compared to other systems and that our system can be adapted to new scenarios with reasonable efforts.

Abstract: Correct information is a vital resource during disasters. Without adequate information, response actions may be ineffective. What is the source of information of emergency management systems? Besides that originated from sensors, the emergency team and the public in general, a very relevant source is government data, such as demographic and geographic data, road maps, etc. The heterogeneity of information formats is a well-known problem that affects organizations and communities that want to access public data. Today, most public agencies provide access to their data, but the great majority is unreadable by automated mechanisms. Besides, most of them do not provide a dictionary meaning for the published content. A solution to this problem is of particular importance to emergency response organizations that need access to all information available to better respond to disasters and crisis. The linked open data (LOD) initiative allows the interconnection of data, using standards in the context of the semantic web approach. In ideal conditions, government agencies publish their public data, thus allowing the use of automated data concerned consumers, whether they are other government agencies or citizens. Efforts aimed to link government data are growing in several countries around the world. This talk presents the LOD concepts and describes an architecture that uses LOD in the design of an Emergency Management System. It describes a scheme for collecting available data from government agencies, such as departments of health, transport, works, that can supply information needs during an emergency response operation.

Abstract: Every day the Fire department of the Netherlands work hard to save people's lives. Therefore, they have been investing in Business Intelligence approaches for several years, to get more information for accident prevention and accident fighting. In this paper, Linked Open Data has been used as a business intelligence approach for the creation of dwelling fire risk profiles based on demographic data. During the research a Proof of Concept showed the appliance of Linked Open Data for this purpose. However the data have some quality mismatches, such as: outdated, accuracy issues and not 100% complete. Evaluation session proofed that the outcomes show similarities with a fire incident map and the gut feeling of several firefighters.