Pattern driven data interoperability in situation awareness systems : a case of the Disaster Community in Uganda

Abstract

Disaster-related information managed by stakeholders is described in multiple schemas, mark-up languages, with different vocabularies, conceptualisations and shared via heterogeneous interfaces. These semantic interoperability barriers further complicate sharing and integration information so that the right people can make the right decisions at the right time. Therefore, this study investigates how patterns can be used to address interoperability concerns in situation awareness systems for Disaster Risk Reduction (DRR). Through a systematic literature review of articles in the disaster management domain, an exploratory study of ontology artefacts was performed to understand the extent of FAIRness for disaster vocabulary and patterns. In addition, we undertake an explanatory case study of the disaster management community in Uganda to study how interoperability barriers contribute to identifying architectural patterns for disaster management systems in line with FAIR principles. Furthermore, a normative case study utilising the eXtreme design methodology is adopted to study patterns reuse for organising knowledge in pattern-driven interoperable systems for disaster risk situation awareness. Results reveal that finding, accessing, and reusing interoperable ontologies and patterns to organise disaster data is difficult because of non-existent DRR domain catalogues. Results also indicate high syntactic and technical interoperability maturity for data in the disaster community. On the contrary, there exist considerable semantic and legal interoperability barriers that hinder data integration and reuse. A mapping of the interoperability challenges in the disaster management community to solutions reveals a potential to reuse established architectural patterns for organising ontology design patterns (ODPs). Finally, the normative case study also identifies thirty-two (32) competency questions, ten (10) reusable patterns and two emerging patterns (i.e. Event classification and quality dependence description ODPs) to characterise disaster risk knowledge in the pattern-driven architecture. Therefore, the illustration of the pattern-driven architecture in the drought risk-informed response context provides a powerful use case for patterns as building blocks to ensure data interoperability in disaster situation awareness systems.