document: Data summaries for on-demand queries over linked data Typical approaches for querying structured Web Data collect ( crawl ) and pre-process ( index ) large amounts of data in a central data repository before allowing for query answering . However , this time-consuming pre-processing phase however leverages the benefits of Linked Data -- where structured data is accessible live and up-to-date at distributed Web resources that may change constantly -- only to a limited degree , as query results can never be current . An ideal query answering system for Linked Data should return current answers in a reasonable amount of time , even on corpora as large as the Web . Query processors evaluating queries directly on the live sources require knowledge of the contents of data sources . In this paper , we develop and evaluate an approximate index structure summarising graph-structured content of sources adhering to Linked Data principles , provide an algorithm for answering conjunctive queries over Linked Data on theWeb exploiting the source summary , and evaluate the system using synthetically generated queries . The experimental results show that our lightweight index structure enables complete and up-to-date query results over Linked Data , while keeping the overhead for querying low and providing a satisfying source ranking at no additional cost .
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