About

The Design Semantics Knowledge graph is an intelligent data network in which meaning, emotion, mythology, and symbols are combined with design elements for the ultimate purpose of creating and analyzing design. Watch the sneak preview video below. 

The network is modularly constructed along the lines of the three-dimensional structure of the Semantic Color Space (Alpaerts & Michiels, 2021). What is innovating about this model is that it distinguishes between different levels of meaning complexity. Level 1 contains only basic polar opposite terms such as dark/light or heavy/lightweight. These form the constituent components for primary keywords, colors, and shapes in level 2. Simple concepts such as enlarge, mass, and primary colors and shapes such as blue and black, circle and square, fall under this category. In turn, these concepts provide the components for the more complex concepts at level 3 with keywords such as powerful, expensive, abundance, or the colors or color combinations dark blue, black-on-green etc. Distinguishing meaning levels is unique in its kind and proves particularly useful for the interpretation of data in design research.

Because keywords and colors are linked by a semantic code, shifts in meaning and nuance can be examined. You can look at how the meaning or emotional effect changes as you make a color darker or lighter, redder or bluer, or what happens when making a shape more angular or upright, etc.  For example, the caring friendliness of pastel rose transforms into a more amicable friendliness when extra red is added. 

Each keyword in the graph and its connection to color and shape have been validated either by research, a scholarly essay or article. Both quote and source are referenced so that a designer can elaborate on their design choices, which is essential when presenting a design to a third party. Using this information, the argumentation as to why a particular color, shape or symbol was chosen, can be legitimately underpinned. 

Previously invisible insights are uncovered with clustering, centrality, and similarity analyses. For example, within a color cluster you can look for the keywords with the most connections. These words can then be interpreted as key meanings for a particular color or shape.

Getting feedback from design professionals is important to us during these early stages of development. If you are a designer, design firm or a teacher at a design academy, college, or university and would like to try the DSK graph free of charge for three months and in return provide feedback to us, then please fill out the participation form.