Data-driven apparel


An algorithm-based t-shirt design, depicting all the historical data of one of the most iconic trail running races, Zegama Aizkorri.


Concept

The proposal aims to capture the entire history of Zegama from its first edition to the present, by representing each and every one of the athletes who have participated throughout the 18 editions of the race, this results in displaying about 7000 participants, specifically placed through an specific algorithm.

For this purpose, a dataset has been created extracting the data from all the classifications of all editions and of the corresponding arrival records of each participant. Using this data set as work material (the arrival times through the 18 editions), each letter that makes up the text represents an edition of the race. Each letter in turn is made up of a specific number of triangles, each triangle being am athlete, and the arrival time of the latter being the one that determines its position within the letter. Thus, the concept that the design aims to convey, as well as the process carried out to achieve it, share the same idea: to show that Zegama is Zegama, thanks to each and every one of those who have participated throughout its history.


Methodology

To generate the design, an algorithm built with Processing generates the typography of the text "ZEGAMA AIZKORRI 2020" using the data of all the classifications, placing in each letter all the participants of each edition (Z for 2019, E for 2018, etc.). The participants are represented by triangles, where the order of position of the participants goes from left to right and from top to bottom, maintaining the distance between them according to the difference of arrival in the classification. The size, color and orientation of each participant is randomly assigned. The design obtained is the result of what is known as generative design, where the "author uses a system, be it a computer program, a machine or another process, which is started with a certain degree of autonomy, thus contributing to the realization of a creation or resulting in a complete creation "(P. Galanter (2016).« Generative Art Theory »).