DataStorm An Ontology-Driven Framework for Cloud-Based Data Analytic Systems

Cloud-based systems have proven to be a powerful technology for building data-intensive applications. However, the process of designing and deploying such applications is still primarily a manual one. There is a need for mechanisms and tools to help automate the required development steps. Using the...

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Bibliographic Details
Main Authors: Wlodarczyk, T W, Chunming Rong, Baodong Jia, Cocanu, L, Nyulas, C I, Musen, M A
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Cloud computing
Computational modeling
Connectors
Data analysis
Hadoop
MapReduce
Ontologies
ontology
OWL
Process control
task-method decomposition
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Summary:Cloud-based systems have proven to be a powerful technology for building data-intensive applications. However, the process of designing and deploying such applications is still primarily a manual one. There is a need for mechanisms and tools to help automate the required development steps. Using the Semantic Web ontology language OWL and the Hadoop platform we have developed a number of models and associated software tools that provide an end-to-end solution for designing and deploying cloud-based systems. This solution supports the construction of detailed models of data dependencies and their validation. It also enables generation and deployment of cloud-based data flows from those models. We illustrate its use for detecting alarm scenarios using data from vast underwater sensor-network.
ISSN:2378-3818
DOI:10.1109/SERVICES.2010.92