The last couple of years it is widely acknowledged that uncertainty and fuzzy extensions to ontology languages, like Description Logics (DLs) and OWL, could play a significant role in the improvement of many Semantic Web (SW) applications. Many of the tasks of SW like trust, matching, merging, ranking usually involve confidence or truth degrees that one requires to represent and reason about. Fuzzy DLs are able to represent vague concepts such as a "Tall" person, a "Hot" place, a "MiddleAged" person, a "near" destination and many more. In the current paper we present a fuzzy extension to the DL SHIN. First, we present the semantics while latter a detailed reasoning algorithm that decides most of the key inference tasks of fuzzy-SHIN. Finally, we briefly present the fuzzy reasoning system FiRE, which implements the proposed algorithm and two use case scenarios where we have applied fuzzy DLs through FiRE.