TY - GEN
T1 - Integration of data mining operations for structural health monitoring
AU - Sonnleitner, E.
AU - Kosorus, H.
AU - Anderlik, S.
AU - Stumptner, R.
AU - Freudenthaler, B.
AU - Allmer, H.
AU - Küng, J.
PY - 2011
Y1 - 2011
N2 - Data Integration is a well elaborated scientific area and one of the most important use cases of the Semantic Web. Techniques developed in this field aim at providing interoperability between heterogeneous data sources. Compared to typical Semantic Web use cases, data integration issues are manifold and also affect applications through their underlying schemas. Civil engineers 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 integration 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 different systems according to their intended operational purpose. This paper presents some practical examples of using Data Mining operations which enable a better understanding of the analysed data and which can be successfully integrated into a unified DSS for SHM.
AB - Data Integration is a well elaborated scientific area and one of the most important use cases of the Semantic Web. Techniques developed in this field aim at providing interoperability between heterogeneous data sources. Compared to typical Semantic Web use cases, data integration issues are manifold and also affect applications through their underlying schemas. Civil engineers 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 integration 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 different systems according to their intended operational purpose. This paper presents some practical examples of using Data Mining operations which enable a better understanding of the analysed data and which can be successfully integrated into a unified DSS for SHM.
UR - http://www.scopus.com/inward/record.url?scp=84866684310&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84866684310
SN - 9781605950532
T3 - Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring
SP - 1325
EP - 1332
BT - Structural Health Monitoring 2011
T2 - 8th International Workshop on Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures
Y2 - 13 September 2011 through 15 September 2011
ER -