Caching and prefetching strategies for SPARQL queries

Abstract

Linked Data repositories offer a wealth of structured facts, useful for a wide array of application scenarios. However, retrieving this data using Sparql queries yields a number of challenges, such as limited endpoint capabilities and availability, or high latency for connecting to it. To cope with these challenges, we argue that it is advantageous to cache data that is relevant for future information needs. However, instead of retaining only results of previously issued queries, we aim at retrieving data that is potentially interesting for subsequent requests in advance. To this end, we present different methods to modify the structure of a query so that the altered query can be used to retrieve additional related information. We evaluate these approaches by applying them to requests found in real-world Sparql query logs. © Springer-Verlag 2013.