Efficient querying of Linked Data by distributing workload

Jan Robas (2016) Efficient querying of Linked Data by distributing workload. MSc thesis.

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Abstract

Online data is presented in different ways and in various forms which are not mutually compatible. This problem is also present in Web APIs, because we usually have to implement a specialised client, suited for the kind of data the Web service is providing. This problem is solved with Linked Data. The problem with Linked Data is the query performance and the availability of remote SPARQL endpoints. With Triple Pattern Fragments we can execute SPARQL queries by transferring some workload to the client, but in contrast we have to transfer more data. The existing AMF extension reduces the amount of HTTP requests and consequently the amount of transferred data on some queries, while increasing the amount of transferred data with others. In this thesis we present our extension, where we try to lower the amount of HTTP requests and the amount of transferred data by extending the metadata with a Bloom filter, containing data, linked with triples on the current page of the Triple Pattern Fragment. We have compared our extension with the AMF extension and achieved encouraging results. We have also proposed a fix for the AMF extension, which is already included in the official repository. Finally, we have developed a simple graphical user interface that enables composition of SPARQL queries and their execution using our extension.

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