Benefits of Linked Data for Interoperability During Crisis Management

Abstract

Gi4DM and ISPRS, WG IV/7KEY WORDS: Linked Data, Ontology, Data sharing, Crisis management, Power cut, Flood, Smart grid, Utility domain ABSTRACT:Floodings represent a permanent risk to the Netherlands in general and to her power supply in particular. Data sharing is essential within this crisis scenario as a power cut affects a great variety of interdependant sectors. Currently used data sharing systems have been shown to hamper interoperability between stakeholders since they lack flexibility and there is no consensus in term definitions and interpretations. The study presented in this paper addresses these challenges by proposing a new data sharing solution based on Linked Data, a method of interlinking data points in a structured way on the web. A conceptual model for two data sharing parties in a flood-caused power cut crisis management scenario was developed to which relevant data were linked. The analysis revealed that the presented data sharing solution burderns its user with extra costs in the short run, but saves resources in the long run by overcoming interoperability problems of the legacy systems. The more stakeholders adopt Linked Data the stronger its benefits for data sharing will become.

A Systematic Review of Ontology-Based River Streamflow and Flood Data Management Challenges

“…Due to the interdisciplinary model across correlated domains, data sharing is a basic need for collaborative decision support systems. Every organization Final Search Query ( ∃C1 ∈ Group-1)AND(∃C2 ∈ Group-2)AND(∃ C3 ∈ Group-3) AND (∀ Group-4) AND (∀ C4 ∈ Group-5) AND (Group-6) [12]. The ontology curate and structure the domain data for effective sharing among the stakeholders and coordinating citizen participators.…”

“…The data is a key to develop efficient decision support systems but the generation of data by different sources raised the issue of inter-operability for a decision support system, especially during an emergency. Re-searchers adapted the ontology-based system for inter-operability challenge as presented in [12] by Roller, R., J. Roes, and E. Verbree. The adaption and utilization of the ontology across multi-platforms resolved the inter-operability challenge and this feature was supported by the semantic web technologies through the use of standardized inter-platform supporting language such XML(eXtensible Markup Language), RDF(Resource Description Framework), OWL(Ontology Web Language).…”

“…in [26] integrated the ontologies representing the distributed water model and provenance information of the heterogeneous water re-sources and information system named "IKNOW", and also evaluated this model from the two real-world water information systems. The ontology-based integration of wireless sensors network is proved through prototype development for the environment modeling in [12]. Flood risk assessment prioritizing and integrating the stakeholder's preference which is normally ignored proved the efficacy of the integration [22].…”

“…Information-centric flood ontology [5] X X X Geo-ontology-based emergency management [10] X X X X X Ontology-based framework for flood disasters [11] X X X X X A semantic sensor web for environmental Decision Support [12] X X X X X Ontology for Sharing and Managing Information in Disaster Response [13] X X X SoKNOS [14] X X X Ontology-based knowledge management framework for a distributed water [15] X X X X framework for flooding forecasting [1] X SSN Ontology [16] X X X Linked data for crisis management [17] X X X X X TABLE 2: Challenges for streamflow and flood data modeling explicit classes and relations. The famous ontology development IDE protégé and Jena Framework provide support for these reasoners.…”

Installed Base Registration of Decentralised Solar Panels With Applications in Crisis Management

“…According to Ramona Roller (2015) Linked Data is supposed to improve Crisis Management because if all stakeholders base the data sharing on the same conceptual model (i.e. using the same terms for concepts and their relationships) then fewer interoperability problems will occur; -Additional datasets can easily be added by generating new triples ; -The data is available to all stakeholders ; -Implicit relationships between data concepts can be made visible and in this way dependencies will become apparent.…”