Service-Oriented Development of Workflow-Based Semantic Reasoning Applications

Service-Oriented Development of Workflow-Based Semantic Reasoning Applications

Alexey Cheptsov (High Performance Computing Center Stuttgart (HLRS), Stuttgart, Germany), Stefan Wesner (Institute of Organisation and Management, University of Ulm, Ulm, Germany) and Bastian Koller (High Performance Computing Center Stuttgart (HLRS), Stuttgart, Germany)
Copyright: © 2014 |Pages: 14
DOI: 10.4018/ijdst.2014010103
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Abstract

The modern Semantic Web scenarios require reasoning algorithms to be flexible, modular, and highly-configurable. A solid approach, followed in the design of the most currently existing reasoners, is not sufficient when dealing with today's challenges of data analysis across multiple sources of heterogeneous data or when the data amount grows to the “Big Data” sizes. The “reasoning as a workflow” concept has attracted a lot of attention in the design of new-generation Semantic Web applications, offering a lot of opportunities to improve both flexibility and scalability of the reasoning process. Considering a single workflow component as a service offers a lot of opportunities for a reasoning algorithm to target a much wider range of potentially enabled Semantic Web use cases by taking benefits of a service-oriented and component-based implementation. We introduce a technique for developing service-oriented Semantic Reasoning applications based on the workflow concept. We also present the Large Knowledge Collider - a software platform for developing workflow-based Semantic Web applications, taking advantages of on-demand high performance computing and cloud infrastructures.
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Towards Semantic Reasoning On The Web Scale

From Web to the Semantic Web

The Web as it is seen by the users “behind the browser” has traditionally been one of the most successful examples of the SOA realization. The possibility to transform the application’s business logic into a set of the linked services supplied with the transparent access to those services over standardized protocols such as HTTP was a key asset for tremendous wide-spread of the Internet worldwide. However the possibility to organize business relationship between the data located on several hosts had been extremely poor. The research seeking for a concept of applying a data model on the Web scale resulted in the Semantic Web – the later advance of the Web, which offers a possibility to extend the Web-enabled data with the annotation of their semantics, thus making the context in which the data is used meaningful for the applications, as elaborated by (Broekstra et al., 2001). Nowadays, there are several existing well-established standards for annotation of data web-wide, such as for example Resource Description Framework (RDF) schema.

The practical value of the Semantic Web is to enable the development of applications that can handle complex human queries based not only on the value of the analyzed data, but also on its meaning. Promotion of such platforms as (Friends-of-a-Friend) FOAF1 at the early stages of the Semantic Web has forced a lot of data providers to actively expose and interlink their data on the Web, which resulted in many problem-oriented data repositories, as for example Linked Life Data (LLD)2, which is a collection of the data for biomedical domain; alone the LLD dataset comprises over one billion web resources presented in RDF. On the other hand, social networks like Twitter or Facebook encourage people to upload there personal data as well, thus drastically increasing the weight of the digital information on the Web.

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