Abstract: In this study, we proposed a modular approach for description logic reasoning to meet the on-demand and scalability requirement semantic-based systems. One typical use of description logic knowledge-base is to support reasoning in semantic-based systems. However, including large description logic knowledge-bases in their complete form in applications would imply unnecessarily huge storage and computational requirement. Therefore, we go beyond the use of static description logic knowledge-base by reusing knowledge dynamically. In particular, we refer to the context-specific contents from large-scale description logic knowledge-bases as description logic modules. A tableau algorithm based on the description logic module representation is given to support modular description logic reasoning. In order to solve the semi-deterministic problem of modular reasoning, we propose an expansion reasoning algorithm for preserving consistency. We also analyzed the time complexity of the modular reasoning algorithm under different conditions. The proposed algorithm improved the performance of description logic reasoning by modulization, especially when the scale of the knowledge-base is very large.