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@@ -29,4 +29,4 @@ In 2008, he, Stefano Ceri, Frank van Harmelen and Dieter Fensel identified this
 > is it possible to make sense in real time of multiple, heterogeneous, gigantic and inevitably noisy and incomplete data streams in order to support the decision  process of extremely large numbers of concurrent users?
 
 
-Since 2028, the Stream Reasoning research community conducted investigations and wrote papers that envision, elaborate, evaluate and discuss many aspects of this research question.  The Stream Reasoning community document that a) the Semantic Web stack can be extended so to incorporate streaming data and events as a first class objects, b) the Stream Reasoning task is feasible, c) the very nature of streaming data offers opportunities to optimize reasoning, d) a combination of deductive and inductive stream reasoning  techniques can cope with incomplete and noisy data. The mature Stream Reasoning solutions got deployed in real scenarios such as Smart City, Social Media Analytics, Oil & Gas, Energy, and Transport.
+Since 2008, the Stream Reasoning research community conducted investigations and wrote papers that envision, elaborate, evaluate and discuss many aspects of this research question.  The Stream Reasoning community document that a) the Semantic Web stack can be extended so to incorporate streaming data and events as a first class objects, b) the Stream Reasoning task is feasible, c) the very nature of streaming data offers opportunities to optimize reasoning, d) a combination of deductive and inductive stream reasoning  techniques can cope with incomplete and noisy data. The mature Stream Reasoning solutions got deployed in real scenarios such as Smart City, Social Media Analytics, Oil & Gas, Energy, and Transport.