This research offers a systematic approach for enhancing design innovation in an e-Design framework through a rich collaboration between cognitive psychology, engineering, and human-computer interaction (HCI). It is expected to transform innovation from an ad hoc process of stumbling upon the key obscure feature needed for innovation to a more methodical search through the space of obscure features, as detailed by an emerging cognitive theory of innovation called the Obscure Features Hypothesis (OFH: McCaffrey, 2011). The OFH states that almost all innovative solutions are built upon an infrequently-noticed or new (i.e., obscure) features of the problem under consideration. Representing the problem’s features in a semantic network and then searching for the obscure ones presents the problem of efficiently presenting and navigating through an intricate semantic network. In order to address this issue, we will develop a software framework (a test-bed) to understand the principle tradeoffs in semantic network visualization; and through a series of user studies we will explore the impact of visual knowledge representation in the design process. This work further extends the synergistic partnership between University of Massachusetts-Amherst (UMass Amherst) and Virginia Tech through the I/UCRC Center for e-Design.