A SOA Based Integration Methodology with Semantic Linking and Resource Fusion

Abstract

Service Oriented Architecture (SOA) promised a loosely-coupled architecture that addresses interoperability issues among heterogeneous applications, and could bring them into the world of Web 2.0. Furthermore, Linked Data is based on Semantic Web technologies, and provides the means to reach the goal of Semantic Web, also known as Web of data, machine-readable Web, or Web 3.0. In military domain, the objective of Army Logistic Management (ALM) is to collect logistic data from Army weapon systems under daily operations, and then to perform statistical analysis to obtain comprehensive information. However, intelligent discovery of logistic information is a significant challenge in ALM scenario with an effective logistic analysis. This study proposes a Multiple-layered Semantic ALM Framework (MSAF) platform, which is based on Semantic Web technologies. It provides an intelligent SOA endpoint for human and machines at any time to access and submit SPARQL queries against a global-scale RDF linked data space and return the upto- date results in RDF formats over HTTP. Moreover, we present an applicable demonstration of ALM scenario based on MSAF, and illustrate a new fusion mechanism for dynamically constructing global Linked Data space to aggregate related RDF dataset from private legacy data sources and public Linked-Data cloud.