The design process of aerospace systems is becoming more and more complex. As the process is progressively becoming enterprise-wide, it involves multiple vendors and encompasses the entire life-cycle of the system, as well as a system-of-systems perspective. The amount of data and information generated under this paradigm has increased exponentially creating a difficult situation as it pertains to data storage, management, and retrieval. Furthermore, the data themselves are not suitable or adequate for use in most cases and must be translated into knowledge with a proper level of abstraction. Adding to the problem is the fact that the knowledge discovery process needed to support the growth of data in aerospace systems design has not been developed to the appropriate level. In fact, important design decisions are often made without sufficient understanding of their overall impact on the aircraft's life, because the data have not been efficiently converted and interpreted in time to support design. In order to make the design process adapt to the life-cycle centric requirement, this thesis proposes a methodology to provide the necessary supporting knowledge for better design decision making. The primary contribution is the establishment of a knowledge engineering framework for design decision support to effectively discover knowledge from the existing data, and efficiently manage and present the knowledge throughout all phases of the aircraft life-cycle. The second contribution is the proposed methodology on the feature generation and exploration, which is used to improve the process of knowledge discovery process significantly. In addition, the proposed work demonstrates several multimedia-based approaches on knowledge presentation.