Integration of Data Mining Operations for Structural Health Monitoring

Abstract

Data Integration is a well elaborated scienti c area and one of the most important use cases of the Semantic Web. Techniques developed in this eld aim at providing interoperability between heterogeneous data sources. Com- pared to typical Semantic Web use cases, data integration issues are manifold and also a ect applications through their underlying schemas. Civil engi- neers specialized in risk and measurement analysis need a reliable Decision Support System (DSS) that integrates various required techniques. Hence, Structural Health Monitoring (SHM) applications tend to adopt typical inte- gration concepts, but not by regarding data and their semantics independent from the application domain. Instead, such a DSS should be accessible in an integrated manner to support the usage of methods and techniques from di erent systems according to their intended operational purpose. This paper presents some practical examples of using Data Mining operations which en- able a better understanding of the analysed data and which can be successfully integrated into a uni ed DSS for SHM.