分析了面向语义Web的直觉模糊粗描述逻辑的研究现状和存在的问题，基于(I, T)-直觉模糊粗集理论将直觉模糊描述逻辑和粗描述逻辑进行了集成，即提出了一种新的直觉模糊粗描述逻辑．针对与本体语言OWL 2等价的描述逻辑SROIQ(D)，对SROIQ(D)进行了扩充，具体提出了直觉模糊粗描述逻辑IFRSROIQ(D)，给出了IFRSROIQ(D)的语法、语义和性质，证明了IFRSROIQ(D)的推理问题（包括知识库可满足性、概念可满足性、概念包含、逻辑推导、ABox一致性推理等）都可以归约到基于完备格的描述逻辑L*-SROIQ(D)上对应的推理．
It is generally accepted that the management of imprecision and vagueness will yield more intelligent and realistic knowledge-based applications. Description Logics (DLs) are suitable, well-known logics for managing structured knowledge that have gained considerable attention the last decade. The work in this paper is directed towards sophisticated formalisms for reasoning under both fuzzy uncertainty and rough uncertainty in ontologies in the Semantic Web. Ontologies play a central role in the development for the Semantic Web, since they provide a precise definition of shared terms in Web resources. The current research progress and the existing problems of intuitionistic fuzzy rough DLs for the Semantic Web are analyzed. An integration between the theories of intuitionistic fuzzy DLs and rough DLs, i.e., intuitionistic fuzzy rough DLs, has been provided based on (I, T)-intuitionistic fuzzy rough set theory. Concretely, we present the intuitionistic fuzzy rough DL IFRSROIQ(D), which is the extension of the expressive DL SROIQ(D) behind OWL 2. It is proved that the reasoning tasks (knowledge base satisfiability, concept satisfiability, subsumption, logical consequence, ABox consistency, BTCB, and BSB reasoning) in the intuitionistic fuzzy rough DL IFRSROIQ(D) may be reduced to the corresponding reasoning in the fuzzy DL over complete lattices L*-SROIQ(D), respectively.