Last year, I attempted to maximise the data-ink of 3 charts here. You can read it to understand more about maximising data-ink and see my previous 3 attempts. After more exposure to charts, I do see that my attempt at the Dot Plot is not a good one as Data Viz Project already has one similar, as seen below:
Given this, I have decided to attempt 3 more.
1. Solid Gauge Chart
Data Viz Project's version:
Here is my first attempt:
Although this version may not exemplify the spirit of maximising data-ink, this allows users to know the values within a glance.
Here is my second attempt:
I think is closer to the idea of maximising data-ink, but it stops being a gauge chart at some point. The use of a gauge chart is not recommended normally unless the purpose is to attract attention. Hence, this can be seen more as a test of theory.
2. Slope Chart
Data Viz Project's version:
Here is my attempt:
The lines are already thin enough. I believe the removal of the axes is not only helpful in the exercise of maximising data-ink, but it also does not remove any detail from the original intent and idea of the slope chart. Therefore, this reduction may be practical in the otherwise already data-ink minimised chart.
3. Organisational Chart
Data Viz Project's version:
Keeping the idea of hierarchy and removing lines, which can be demonstrated in other ways, I think my attempt on the org chart keeps the original intent of levels and layers. However, Tutfe's discussion in Beautiful Evidence on how arrows help with causal linking does put a dent in my attempt. As is often, in a large organisation, the hierarchy may not be as simple as the sample image.
All in all, these reimaginations have allowed me to understand more about how theories can be applied, but theories often cannot be carried out wholesale in practicality.