  In this paper, we investigate the problem of evaluating Basic Graph Patterns
(BGP, for short, a subclass of SPARQL queries) over dynamic Linked Data graphs;
i.e., Linked Data graphs that are continuously updated. We consider a setting
where the updates are continuously received through a stream of messages and
support both insertions and deletions of triples (updates are straightforwardly
handled as a combination of deletions and insertions). In this context, we
propose a set of in-memory algorithms minimizing the cached data for
efficiently and continuously answering main subclasses of BGP queries. The
queries are typically submitted into a system and continuously result the delta
answers while the update messages are processed. Consolidating all the
historical delta answers, the algorithms ensure that the answer of each query
is constructed at any given time.
