Abstract
Handling large knowledge bases of information from different domains such as the World Wide Web is a complex problem addressed in the Resource Description Framework (RDF) by adding semantic meaning to the data itself. The amount of linked data has brought with it a number of specialized databases that are capable of storing and processing RDF data, called RDF stores. We explore the RDF store landscape with the aim of finding an RDF store that sufficiently meets the storage needs of an enhanced living environment, more concretely the requirements of a Smart Space platform aimed at running on a cluster set up of low-power hardware that can be run locally entirely at home with the purpose of logging data for a reactive assistive system involving, e.g., activity recognition or domotics. We present a literature analysis of RDF stores and identify promising candidates for implementation of consumer Smart Spaces. Based on the insights provided with our study, we conclude by suggesting different relevant aspects of RDF storage systems that need to be considered in Ambient Assisted Living environments and a comparison of available solutions.
Highlights
With the advent of the open Web and the large amounts of information that it has brought with it, a need for technologies that can handle large quantities of unstructured data in an automated fashion has arisen
The need for these storage systems capable of processing large amount of Resource Description Framework (RDF) data is evident by looking at the great effort that has been invested in a whole range of production system ready, RDF stores [24,32,42]
The major difference was that 4store stores triples as quads, while librdf stores triples as triple statements extended with the context field
Summary
With the advent of the open Web and the large amounts of information that it has brought with it, a need for technologies that can handle large quantities of unstructured data in an automated fashion has arisen. As a solution in order to mitigate some of the complexities involved when intelligently handling large amounts of knowledge. Storage and retrieval of information in the RDF format is most often performed by using specialised storage systems called RDF stores. The need for these storage systems capable of processing large amount of RDF data is evident by looking at the great effort that has been invested in a whole range of production system ready, RDF stores [24,32,42]
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