  Data-driven conceptual design methods and tools aim to inspire human ideation
for new design concepts by providing external inspirational stimuli. In prior
studies, the stimuli have been limited in terms of coverage, granularity, and
retrieval guidance. Here, we present a knowledge based expert system that
provides design stimuli across the semantic, document and field levels
simultaneously from all fields of engineering and technology and that follows
creativity theories to guide the retrieval and use of stimuli according to the
knowledge distance. The system is centered on the use of a network of all
technology fields in the patent classification system, to store and organize
the world's cumulative data on the technological knowledge, concepts, and
solutions in the total patent database according to statistically estimated
knowledge distance between technology fields. In turn, knowledge distance
guides the network-based exploration and retrieval of inspirational stimuli for
inferences across near and far fields to generate new design ideas by analogy
and combination. With two case studies, we showcase the effectiveness of using
the system to explore and retrieve multilevel inspirational stimuli and
generate new design ideas for both problem solving and open ended innovation.
These case studies also demonstrate the computer aided ideation process, which
is data-driven, computationally augmented, theoretically grounded, visually
inspiring, and rapid.
