Data-driven logotype design

In this work we create another meaning to typography and explore the intersection between type design, visual identity design, and information visualisation. We explore how data can influence the design of a logotype, and how can a logotype convey information. We selected our university − the University of Coimbra (UC) − as case study and developed a data-driven logotype for its diverse faculties. The design of the proposed logotype is influenced by the current spectrum of students in each faculty. It is also able to incorporate and unify the different faculties in a coherent fashion while changing over time to adapt to the input data regarding the students. The result is a dynamic logotype capable of representing the different faculties of the university.

Figure 1

Video of the final results




We compiled data on the number of students in each gender and nationality. Among the available data we hoped that these two variables were representative of the students of each faculty. The used data refers to the year 2015 and it was collected mainly from the web page of the University of Coimbra. We decided to only use faculties with bachelor and master degrees. In the end, we considered eight faculties: Arts and Humanities (FLUC), Law (FDUC), Science and Technology (FCTUC), Pharmacy (FFUC), Economics (FEUC), Psychology and Education Sciences (FPCEUC), Sports Sciences and Physical Education (FCDEFUC), and Medicine (FMUC). Table I shows the information collected. Regarding nation- ality, we found four groups corresponding to: Portuguese students (PT), students from countries with Portuguese as official language (PL), from countries in the European Union (EU), and from other countries (O).


In University of Coimbra there is a big range of students. Under those circumstances it becomes natural to choose various typefaces to represent this diversity. To achieve this, we picked four categories of typography classification − garaldes, reales, didones and linear − and for each one of them we adopted some typefaces. The logotype created for each faculty was developed from its acronym. For each letter of the acronym we overprinted the chosen fonts (figure 2) . The main goal is to uniform the group’s characteristics of the chosen fonts.

Figure 2

Creation of the letterforms by overprinting a selection of fonts.




After the letterforms were produced we needed a way to fill the shapes. The next step was the development of a grid over the shape previously generated. We needed to represent three variables: (i) the nationality, (ii) the gender and (iii) the number of students.  Evidently, we related the number of students with the density (figure 3) of the elements.

Figure 3

Representing the number of students using density

Throughout the development of this project we test different approaches, but in the end we established a module previously drawn to each nationality (figure 4) and colour to each gender. Given that we could combine the two variables.

Figure 4

Representing the students’ nationality using graphic elements

In order to distinguish the elements of each gender we decided to use layers (figure 5). In other words, we applied the elements in two layers with the shape of the letterforms previously created, each one for each gender. The elements were drawn from top to bottom and left to right. The layers were superimposed, but not aligned. In order to visualise all the elements we applied the multiply effect.

Figure 5

Representing the students’ gender using colour

For each faculty the maximum area occupied by the characters in each letter is associated to the maximum number of students by gender. We have also determined the minimum allowed a greater contrast between densities because it limits the range of values for density.


In the end we arrive at the logotypes in figure 6 and 7. The colour red and blue represent the amount of women and men respectively. For modules, the right triangle represents Portuguese students, the quarter of a circle represents students from countries with Portuguese as official language, the other triangle represents students from within the European Union and a line represents students from other countries.

Figure 6

Logotypes generated in the final iteration. The modules represent the students’ nationalities; the colours represent the students’ genders; and the modules’ density represents the number of students.

Now, thanks to the rotation in modules it is possible to visualise each layer and the intersection between them. Thanks to the variation of density we noticed that FCTUC is the faculty with more students and, on the other hand, FCDEFUC and FPCEUC are two of those with less. Looking at the logotypes, we can also observe that the Faculty of Psychology and Education Sciences (FPCEUC) have more women than men. Furthermore, as it was predictable, the Sports Sciences and Physical Education (FCDEFUC) are more male students.

Figure 7

Logotype of Science and Tecnology faculty  generated in the final iteration

In the development of this project we noticed the obligation to test the minimum and maximum densities. In order to reduce the detail and reduce sizes we should decrease the minimum and maximum densities. In figure 8, we have five different levels of density being represented. In this iteration we also tested the area that each module occupies in the grid space where it is placed. For a better understanding, some tests are shown in figure 9.

Figure 8

Glyphs for letter F with different levels of modules’ density

Figure 9

Glyphs for letter F with different modules’ sizes


To appear in


Jéssica Parente, Tiago Martins, and João Bicker. Data-driven Logotype Design. In 22 International Conference Information Visualisation, 2018