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Novel Models and Architectures for Distributed Semantic Data Management

Authors:
Kuldeep Reddy

Keywords: distributed semantic data management; actor- based systems; ontology learning; ontology noise removal; ontology alignment; hadoop map-reduce; interactive sparql querying

Abstract:
Semantic data management refers to a range of techniques for the manipulation and usage of data based on its meaning and its rapid growth gives rise to the problems of building novel models and architectures for its distributed management allowing efficient query processing and reasoning. The first part of the work proposes an actor model for distributed semantic data management based on the concept of liquid architectures proposing an actor programming frame- work and execution environment to store, query and reason over structured RDF data. The motivation being to provide a low latency, high throughput distributed platform for semantic data. The second part of the work proposes a pay-as-you-go model and architecture for providing OWL-based semantics as a service including ontology construction, alignment and noise removal from text documents according to the query workload using hadoop map-reduce framework. The third part of the work proposes a query model, including four initial approaches, to generate interactive suggestions as an aid to the user for better formulation of SPARQL queries.

Pages: 68 to 73

Copyright: Copyright (c) IARIA, 2013

Publication date: September 29, 2013

Published in: conference

ISSN: 2308-4510

ISBN: 978-1-61208-293-6

Location: Porto, Portugal

Dates: from September 29, 2013 to October 3, 2013