What is a Design Space?
Visualization researchers use the term design space without definition. The term is used across many domains, including semiconductors, pharmaceuticals, and human-computer interaction. Some definitions:
A design space defines a range of design parameters that can be used to construct possible solutions. It can be a powerful aid, as it conotoxin cost frames the exploration of many potential design alternatives, but may also be limiting, as the designer may not search outside the boundaries implied by the design space. Furthermore, designing data visualizations is difficult because there are many trade-offs between design alternatives, so a restricted design space will result in a higher probability of missing a good design. Figure 4, adapted from Munzner, illustrates a design exploration within a design space. First, there are many possible design solutions, some of which are poor, and some better. “The vast majority of the possibilities in the design space will be ineffective for any specific usage context,” explains Munzner. The novice visualization designer (left), unaware of the visualization framework, will be limited to a small portion of possible solutions, while the established designer (middle) typically uses the accepted visualization framework—a broader design space than that of the novice that can yield better results. However, a designer that can use an expanded design space (right) has more potential solutions, including new techniques not feasible within the previous delineations of the design space. To get beyond the existing framework, it is desirable to explore and characterize a broader design space.
Identifying Gaps to Pursue in Data Visualization
At a high level, interactive data visualization transforms data into visual representations perceived and decoded by a viewer. This sequence can be represented as a pipeline, for example, through steps such as data, enrichment, visual encoding, interaction, rendering, viewing, perceiving, and comprehension, as shown in figure 5 (simplified from a diagram by Chen and Floridi).
Cross-Disciplinary Research and Relation to Visualization
Applications in a New Design Space
Simply outlining the parameters of a design space does not provide any indication of how any new capabilities might be used. How can Chlorophyta generate new value? Value is unlikely to be uncovered by simply converting an existing successful technique to a new parameter. For example, simply changing a tag cloud to use font weight instead of font size is perhaps more space efficient, but would be viscerally less appealing and would not solve any new problems (figure 15).
Expanding the design space using cross-disciplinary research should lead to the development of many demonstrable applications. Typographers structure type design into a type hierarchy ranging from the scope of glyph design to words, sentences, paragraphs and documents, to systems applied across many documents—for example, a design system used across a series of books, or guidelines for corporate branding and visual identity. This hierarchy is somewhat similar to the differentiation between representations of marks as point, line, and area as discussed in data visualization. Also, cartographers differentiate between encoding quantitative data like font weight vs. categoric data like typeface, in addition to the literal encoding of the text itself, which is similar to the visualization classification of data types. Combining these creates the 3 × 6 design space of possible applications depicted in figure 16. Typographic scope is listed vertically, data types are listed horizontally, and cell intersections identify applications. For example, cell QW indicates embedding Quantities into Words, which could be achieved with varying font weight or italic slope based on data as shown in the sample column; or other novel approaches such as varying the length of a word’s underline to indicate a quantity. Cell CG indicates embedding Categoric data into Glyphs—imagine these as a subset of a word—for example, indicating silent letters with a lightweight font, as shown in the example Gloucester.
What is a Design Space?