Money Leave(s) Portugal: an Aesthetic Exploration of Public Investments

Data Visualization

The visualization had the main purpose of representing the investments made in Portugal’s different activity sectors. We aimed to reveal the dimension and distribution of the contracts applied in these sectors, particularly the monetary volumes that were invested. We chose to use this data to raise awareness about one invisible pattern of our society, the administration of the public money. Despite being public and accessible to all, in reality, this information tends to be ignored by the majority. Given that the central attribute of the dataset that we intended to highlight was the money employed throughout the country, we opted for a metaphorical approach to represent the physical object in our focus: the money bills. We focused on the plants of which the notes are made (cotton fiber and linen), more specifically, on their leaves’ growing process, as a metaphor for the increasing total of the money invested in contracts day after day. The visual translation of our approach will be further discussed in the next section.

 

Leaves

 

The main elements of our visualization were thought to represent the money involved in Portugal as the result of the multiple public contracts yield. To this end, we represent the money growth through the plant’s growth, specifically, its leaf. A leaf translates the total amount invested in a given district for a given sector. The growth of this value is mapped to the growth of the leaf, with lower values having less visual prominence (smaller elements) and, in contrast, considerably higher values having more visual prominence (larger elements). This cumulative approach to represent the daily new data in favor of an incremental representation had to take into account the scalability of the visualization; otherwise, the visualization would become unreadable after several days of collecting data due to the increasing visual clutter generated by the leaves’ overlaps. The total number is deconstructed, and a distinct element was created for each one of its digit positions. In the case of units and tens, the corresponding elements are combined through smaller internal filled circles and external stroked circles, respectively. The amount of elements for each digit position represents the corresponding digit value (e.g. the number 931 would be represented with 9 elements for the hundreds, 4 elements for the tens and 2 elements for the units). In the event of digit zero for a given position, no element of the corresponding position is represented. Figure 1 can be consulted for all possible combinations of all position elements and presents an example of a leaf representing the amount of 9999999€.

While the drawing of every leaf may result in visual clutter, the different types of leaves can still be identified when drawn together, keeping their legibility regardless of representing a low or high value. This is similar to plant fields, that regardless of their size when grown in a condensed place, manifest themselves as a whole. We intended to translate this visual phenomenon into the created visualizations, so that the viewers, in their first interaction, would initially see it as a whole and only through exploration could the distinction between leaves be perceived.

 

Figure 1


All leaf elements variations (top). Example of leaf representing the amount of 9999999€ (bottom).

 

Structure

 

The visualization maps the contracts into a modular grid where each module represents a Portugal district. The layout of the modules, with a distribution of 36 (districts) + 2 (autonomous regions of the Azores and Madeira) is intended to resemble the geography of Portugal. The districts are arranged in order to approximate the relative position of each district in Portugal as closely as possible. An aesthetic decision was made to place the autonomous regions underneath the districts, to allow for a more homogeneous framing of the entire canvas data. In order to more easily distinguish the commercial area to which a given contract applies, the 45 established categories of CPV were grouped into 12 groups: (1) Health, (2) Food, (3) Commerce, (4) Communication, (5) Industry, (6) Transports, (7) Culture, (8) Construction, (9) Technology, (10) Education, (11) Consulting and (12) Society, which can then be further distinguished by the contract type of procedure 2. There are five types of procedures, with different criteria and rules of application: (A) Open procedure, (B) Direct award, (C) Prior consultation, (D) Restricted procedure, (E) Framework Agreement.

The CPV grouping (1 to 12) and their further distinction per type of procedure (A to E) is applied to each grid module, and it is responsible for placing and representing the visual element that translates the amount employed in the contracts. The CPV groups are translated into 12 points, arranged in an alternating formation (2,3,2,3,2) from top left to bottom right. Taking the point of the corresponding CPV group as reference, the distinction between the types of procedures is made through the orientation in which its corresponding leaf is represented. Starting on the orientation of the vertical axis, in a radial layout, the five types are equally spaced lines arranged radially around the CPV group point. The overall structure of the visualization, namely the districts, the CPVs groups and the type of procedures placings are further explained in Fig. 2.

 

Figure 2

Visualization structure responsible for the contracts. The CPV Groups (1-12) and types of procedures (A-E) correspond to the same numbers and letters previously used

 

As stated previously, new contracts are collected and the visualization updated daily, and this update is reflected through two modes. At a given interval, the visualization changes between a cumulative view and a daily view, either representing the total of contracts since its initialization, or just the contracts collected for the present day. This interchange was devised to allow the user to perceive the daily increase of public contracts more easily. One state of the visualization can be seen in Figure 3.

 

Figure 3

Visualization screenshot presenting all contracts at the 1st and 10th of January.

 

 

To be published in
IV2020 – 24th International Conference Information Visualisation

Author

Pedro Silva

Pedro Martins

Penousal Machado


Date

10/08/2020


Acknowledgements

This work is funded by national funds through the FCT—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. The first author is funded by the Fundação para a Ciência e Tecnologia (FCT), Portugal under the grant SFRH/BD/144283/2019