This paper describes a showcase of Computational Design projects from three diferent areas: Type design, Icon design and Flag Design. The nature of these tools is also diferent, going from a creativity support tool to a fully automatic system. We analyse these tools in terms of use of knowledge and user interaction. The ability to create new concepts by making connections between existing ones is, in part, related to our creative behavior [1]. Such ability is highly needed in design processes and has to be considered when implementing Computational Design systems. The use of knowledge-based systems has great potential in computational design, especially for solving creative problems based on previous solutions. In this paper, we describe a showcase of three projects from three diferent domains: type design, icon design and flag design. In this section, we describe the projects featured in the showcase, which consist of a creativity support tool (TypeAdviser), a co-creative system (Emojinating) and a fully automatic one (Everchanging flags ). All the projects use knowledge to help or guide the process of design in a computational system.
A typeface is a set of characters that work as a family – even though they all look diferent,
they share characteristics. The first project that we want to describe, Typeadviser [
The user inputs previously drawn vectorial glyphs and then identify their parts. The system
then generates other letters, based on the predefined rules of part-sharing – this is controlled
by the Part-sharing component, which was built using type design principles. The Adviser
uses Self-Organizing Maps (soms) to suggest similar designs to the user. A som is used to
produce a similarity map of diferent styles of character for each letter, grouping similar styles.
With this approach, the user is able to draw a letter and then see possibilities for the other
letters, based on the drawn one. There are two main uses for this: (i) to serve as inspiration by
allowing the designer to see characters of similar typefaces; but also (ii) to help in distancing the
typeface being designed from existing ones. Our system could be combined with approaches
for computational generation of glyphs [
The visual representation of concepts or ideas through the use of graphic shapes has always
been explored in the history of humanity and has a key role in how we share information
among each other. This is the base idea behind our work on computational generation of
visual representations of concepts. We follow an approach that explores visual blending of
existing symbols to represent new concepts. Our contributions in this domain started with
a low scale system, in which three concepts (pig, angel and cactus) and corresponding visual
representations were used to produce combinations [
The last project that we want to present addresses flag design. Flags have an important role
when it comes to constructing and maintaining a sense of identity of a nation [
We briefly described three projects ( TypeAdviser, Emojinating and Ever-changing Flags) from three diferent domains ( Type Design, Icon Design and Flag Design). All these projects have one thing in common – they all use domain knowledge to guide and/or aid in a process of design. However, the way that they integrate and make use of this knowledge is not the same.
One issue with implementing systems for computational design is that they address tasks that can be seen as open-ended – there might be no optimal solution since they often depend on user preferences. For reason, the relation between user and system is of extreme importance when developing such a system. This relation has an obvious impact on the way a system is designed, especially concerning the use of prior knowledge. By analysing the described projects, it is easy to identify several ways of using knowledge. TypeAdviser uses knowledge to reduce the time spent in designing a typeface but also to present the user characters of similar style, thus making it easier to either come closer to or avoid resemblances to existing typefaces. On the other hand, while TypeAviser uses knowledge to merely aid the process of design, Emojinating highly relies on domain knowledge. The capability of reaching solution that represents a user-introduced concept depends on the existence of such knowledge. Moreover, TypeAviser can only be seen as a creativity support tool. In contrast, Emojinating has a more cooperative relation with the user, creating a co-creative dynamic between the two. In addition to this, Emojinating is able to adapt itself to the user by changing its knowledge – e.g. by a keeping a record of what sort of solutions match the user preferences.
The third project (Ever-changing Flags) can be placed in the opposite end of the spectrum to TypeAdviser – it requires very little of the user. The system uses the domain knowledge as a guide to produce its own solutions – e.g. using elements (or part of them) that have a certain meaning to assign a similar meaning to a flag. In doing so, the only thing required of the user is the selection of which country the system should produce a flag for.
Another interesting aspect is the possible applications of these systems. One example is the
use of Emojinating engine for purposes of information visualization [
This work is partially funded by the Foundation for Science and Technology, I.P., within the scope of the project CISUC - UID/CEC/00326/2020 and by European Social Fund, through the Regional Operational Program Centro 2020, and under the grant SFRH/BD/120905/2016.