There are many facets to creativity, and the topic has a profound impact on society. Substantial and sustained study on creativity has been undertaken, and much is now known about the fundamentals and how creativity can be augmented. To draw these elements together, a framework was developed called the creativity diamond, formulated on the basis of reviews of prior work, as well as the consideration of 20 PhD studies on the topics of creativity, design, innovation, and product development. The framework embodies the principles that quantity of ideas breeds quality through selection, and that a range of creativity tools can provoke additional ideas to augment our innate creativity. The creativity diamond proposed is a tool consisting of a divergent phase associated with the development of many distinctive ideas and a convergent phase associated with the refinement of ideas. The creativity diamond framework can be used to prompt and help select which tool or approach to use in a creative environment for innovative tasks. The framework has now been used by many students and professionals in diverse contexts.

In the field of content generation by machine, the state-of-the-art text-to-image model, DALL⋅E, has advanced and diverse capacities for the combinational image generation with specific textual prompts. The images generated by DALL⋅E seem to exhibit an appreciable level of combinational creativity close to that of humans in terms of visualizing a combinational idea. Although there are several common metrics which can be applied to assess the quality of the images generated by generative models, such as IS, FID, GIQA, and CLIP, it is unclear whether these metrics are equally applicable to assessing images containing combinational creativity. In this study, we collected the generated image data from machine (DALL⋅E) and human designers, respectively. The results of group ranking in the Consensual Assessment Technique (CAT) and the Turing Test (TT) were used as the benchmarks to assess the combinational creativity. Considering the metrics’ mathematical principles and different starting points in evaluating image quality, we introduced coincident rate (CR) and average rank variation (ARV) which are two comparable spaces. An experiment to calculate the consistency of group ranking of each metric by comparing the benchmarks then was conducted. By comparing the consistency results of CR and ARV on group ranking, we summarized the applicability of the existing evaluation metrics in assessing generative images containing combinational creativity. In the four metrics, GIQA performed the closest consistency to the CAT and TT. It shows the potential as an automated assessment for images containing combinational creativity, which can be used to evaluate the images containing combinational creativity in the relevant task of design and engineering such as conceptual sketch, digital design image, and prototyping image.

Data-driven design is a process to reuse data sources and provide valuable information to provoke creative ideas in the stages of design. However, existing semantic networks for design creativity are built on data sources restricted to technological and scientific information. Existing studies build the edges of a semantic network on statistical or semantic relationships, which are less likely to make full use of the benefits from both types of relationships and discover implicit knowledge for design creativity. Therefore, to overcome the gaps, we constructed WikiLink, a semantic network based on Wikipedia, which is an integrated source of general knowledge and specific knowledge, with broad coverage of disciplines. The weight in WikiLink fuses both the statistic and semantic weights between concepts instead of simply one type of weight, and four algorithms are developed for inspiring new ideas. Evaluation experiments are undertaken, and the results show that the network is characterised by high coverage of terms, relationships and disciplines, which demonstrates and supports the network’s effectiveness and usefulness. A demonstration and case study results indicate that WikiLink can serve as an idea generation tool for creativity in conceptual design. The source code of WikiLink and the backend data are provided open-source for more users to explore and develop.