The Design Semantics Knowledge Graph maps visual sign systems, meaning, and emotional effect, into a coherent, intelligent data network, for the ultimate purpose of creating designs that are meaningful, easy to use, and fascilitating well-being. Watch the sneak preview video below.
With its innovating architecture, it constitutes a practical tool that enhances the interpretation of data in design.
Optimal disambiguation of meaning: eliminate misunderstandings during a design process.
Shifts in meaning: look at how the meaning and emotional effect change.
Storylines: mapping out routes of meaning.
Corroborating your design choices: validation of data.
Culture and context: a number of additional explanatory properties.
Research and analysis: new and extraordinary opportunities.
At its core is the Semantic Colour Space (Alpaerts & Michiels, 2021), a ground-breaking design tool that brings together over thirty years of research, creative exploration, and teaching practice into one practical framework to explore the relationship between design elements, meaning, and emotion. Rather than treating visual elements as isolated components, the Semantic Colour Space frames them as interconnected and synaesthetic parts of a semantic system. Grounded in a multidisciplinary foundation and drawing heavily from scientific disciplines, especially linguistic semantics, semiotics, cognitive psychology, evolutionary biology, anthropology, and systems theory, the Semantic Colour Space provides designers with both a conceptual framework and a practical tool to start a design praxis where perception, emotion, and meaning work hand in hand. This approach allows for a move toward a human-centred design, where the main concern is how artefacts are experienced, understood, used, and integrated into people’s lives.
One of the specific advantages of this graph is that it exposes ambiguity in meaning. After all, a given word can have many connotations, or even convey something completely different for various people. For example, the keyword “friendly” could have as many as five different interpretations that become visible through the clusters, showing the best approximation in meaning and meaning nuance, useful when working together with a design team and client. Right from the start it enables avoiding misconceptions during a design process, thus improving communication between different stakeholders.
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.
Not only can information about meaning be retrieved, throughout the network, routes can be mapped out that form the basis for storylines.
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.
In addition, each keyword is accompanied by a number of additional properties such as culture and context specific data, the design application, vocabulary, the semantic code, and a color value.
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.
As we speak, the graph contains 1,466 keywords and 14,737 connections, 128 colors and color combinations, 32 parameters of shape, and continues to grow. In fact, the graph is a live network that is constantly expanding with new data, new insights, and research. The graph database technology offers unprecedented opportunities in research and design. In the future, search queries will be expanded and it will become easy to locate nodes and relationships within the graph and data. Furthermore, it will be possible to zoom in on focused graph views and plot pathways that form storylines.
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