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Preparing legend of detail for the exhibition display.

Experimented the marbling with watercolour paints. I wanted to see how the colours would appear on prints. I tried with mixing the paints both in pure water and paint dispersant. For the result, the paint didn’t spread out on the surface. If it was successful, the colour mixing would’ve been more easier.

Mini sample pieces ✨✨✨

Paper pretreated with mordant and now ready for the marbling print making!

#process

The first trial on marbling based on my own self-portrait which is data #9

I’ve tried it with a small number of ingredients just to see how it would appear

after the test, I found out to two things to improve on

1. sadly, all the paints sank down in the water base so I could only get a thin layer of paints on the surface. It might happen because I didn’t use enough chemicals for the water base or I didn’t wait for enough until the water to be thickened up

2. as expected the colour appeared differently from my colour palette

It would be hard to get the exact colour on the colour palette because it was set on a computer.

suggestions:

try to make a water base with different ratio

re-set a colour palette range by trace back the colours that are printed on the paper

started making a visual profile of each data so I can easily understand the data that are coded on excel spread sheet and also needed it to use as a guide for marbling

I will make a visual profile for each data as above

Roughly made a colour palette guide for marbling

Each characteristic of the data will be represented by colours that I’ve chosen

The base of the artwork will depend on its medium

data that is created with

-an analogue technique will be based on a brown/natural paper

-a digital technique will be based on a white paper

all other colours will be used as above

but no colours will be used for neutral gender

because the colour palette was made on a computer

it might appear differently in reality

#vdta18 colour palette

Week 6 - Data Visualising program ‘Processing’

In class, we had a look at the program called Processing by learning insert coding into the program to create the graphic.

It was my very first time using/come across with the term ‘coding’ so it took a bit of time to understand the program. Anyhow it was interesting to learn new techniques to explore data visualisation.

#belatedpost

A Bogota designer promotes DIY data viz using balloons, tape, and other things you can find in your drawers.

Group Presentaion

For the first assignment, our group decided to present the demographic data of the artists featured in the NGV Triennial 2018 exhibition.

We decided few factors to be conveyed in our visual demographic map. We chose to demonstrate a year of birth, place of birth, and the gender of each artist. We decided to use place of birth as our starting point and to create links and patterns from there through the addition of the remaining categories.

Progress

We drew a world map on a board and started with pinning down the place of birth of each artist who is listed in our data sheet.

To represent the age of the artists, we divided the age groups by decades using a different colour of yarns to link each artist of the age group.

To represent the gender of the artist, we coloured the head of the pin in yellow(to represent female) and pink(to represent male).

Conclusion

We found few facts through the process of visualisation of data:

that the majority of the represented artists were born in Australia, and that Asia and Africa are under-represented in this particular exhibition.

The largest network out of each decade is the 1970s, and Generation X is over-represented, as most of the artists were born from 1960-1980.

there is eight more female artist than male, however there is roughly an even number of each.

Future suggestions:

If we were to further develop this project in the future, we could consider representing the data on a globe as opposed to a flat sheet, in order to give a more accurate representation of each artist’s location in relation to each other, and the networks of age groups could be optimised using the travelling salesman problem. Working with a larger area and using thinner thread would make for easier application of data and remove some of the clutter. We could also consider scaling the countries on the map based on the number of artists from each country. We could also consider adding another data category such as using the length of the pins to convey how many works each artist had in the exhibition, and think about ways in which we could connect the artist in ways other than just their age.

#vdta #vdta2018 #assignment1