Addressing Streaming and Historical Data in OBDA Systems: Optique's Approach
نویسندگان
چکیده
In large companies such as Siemens and Statoil monitoring tasks are of great importance, e.g., Siemens does monitoring of turbines and Statoil of oil behaviour in wells. This tasks bring up importance of both streaming and historical (temporal) data in the Big Data challenge for industries. We present the Optique project that addresses this problem by developing an Ontology Based Data Access (OBDA) system that incorporates novel tools and methodologies for processing and analyses of temporal and streaming data. In particular, we advocate for modelling time time aware data by temporal RDF and reduce monitoring tasks to knowledge discovery and data mining.
منابع مشابه
Optique: OBDA Solution for Big Data
1 Motivations and Challenges Accessing the relevant data in Big Data scenarios is increasingly difficult both for end-user and IT-experts, due to the volume, variety, and velocity dimensions of Big Data.This brings a hight cost overhead in data access for large enterprises. For instance, in the oil and gas industry, IT-experts spend 30–70% of their time gathering and assessing the quality of da...
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Real-time analytics that requires integration and aggregation of heterogeneous and distributed streaming and static data is a typical task in many industrial scenarios such as diagnostics of turbines in Siemens. OBDA approach has a great potential to facilitate such tasks; however, it has a number of limitations in dealing with analytics that restrict its use in important industrial application...
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