2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS) (2015)
Dec. 11, 2015 to Dec. 13, 2015
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DSDIS.2015.43
Risk analysis has become recently an important activity in many industrial domains: mining, off-shore drilling, health services etc. For short, risk analysis studies the relationship between causes of an accident and the severity of its consequences. It comes as no surprise that Risk Management Information Systems (RMIS) for tracking and reporting the costs of preventing accidents and mitigating the consequences of critical events have attracted a lot of research and development efforts. The amount and especially the complexity of data in a typical RMIS make such systems very difficult to design. In this paper we present a popular model for risk management data representation, the bowtie model, which is almost the de facto model in risk management systems. The bowtie model we present is inherently a directed graph. Then we show how we define and use an extension of the XQuery language, called TreXQuery, to perform intricate searching of graph models in risk management systems.
Data models, Risk management, Standards, Analytical models, Accidents, Registers
I. E. Iacob and A. Apostolou, "Scalable Data Representation in Risk Management Information Systems Using an XQuery Extension," 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS), Sydney, Australia, 2015, pp. 89-96.