Ontology-Based Integration of Streaming and Static Relational Data with Optique

Evgeny Kharlamov, Christoforos Svingos, Dmitriy Zheleznyakov, Ian Horrocks, Yannis Ioannidis, Ralf Moeller, Sebastian Brandt, Ernesto Jimenez-Ruiz, Yannis Kotidis, Steffen Lamparter, Theofilos Mailis, Christian Neuenstadt (+2 others)
2016 Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16  
Real-time processing of data coming from multiple heterogeneous data streams and static databases is a typical task in many industrial scenarios such as diagnostics of large machines. A complex diagnostic task may require a collection of up to hundreds of queries over such data. Although many of these queries retrieve data of the same kind, such as temperature measurements, they access structurally different data sources. In this work we show how Semantic Technologies implemented in our system
more » ... PTIQUE can simplify such complex diagnostics by providing an abstraction layerontology-that integrates heterogeneous data. In a nutshell, OP-TIQUE allows complex diagnostic tasks to be expressed with just a few high-level semantic queries. The system can then automatically enrich these queries, translate them into a collection with a large number of low-level data queries, and finally optimise and efficiently execute the collection in a heavily distributed environment. We will demo the benefits of OPTIQUE on a real world scenario from Siemens.
doi:10.1145/2882903.2899385 dblp:conf/sigmod/KharlamovBJKLMN16 fatcat:r5hcgvmrurbe7a6rxjenrcn4xq