Processing

Processing is an open source programming language developed for visual design, new media art and electronic arts. It is all about coding, programming, gathering and visualizing new data or data that already exists. Thus, it can be considered an electronic sketchbook, which refers to collective creativity. The software was created to give designers, artists the possibility to learn how to code and create visual art in programming. Processing has been developed by Casey Reas, conceptual artist, and Benjamin Fry, expert in data vizualisation, which were both formerly part of the Aesthetics and Computation Group at the MIT Media Lab. Measurement on screen in processing is made with pixels, which is a little dot containing colour, and the language it builds on, is Java. The basic functions of processing allow you to draw shapes, set colours and calculate numbers. It is essential that the syntax of a line of code, an instruction, is correct for processing to work. It can be downloaded from processing.org, where the work of others is visible.

Open processing is a platform where everybody can share and exchange sketches of programming in order to improve and polish his skills. Processing is all about trying, learning and exercising. The more you experiment, the better you get. Open processing allows its users to collaborate and to get help from other people.

Some examples of visual artists working with codes are for example, Quayola’s work 'Strata Nr. 3' created in London, which represents the ceiling of the Sistine Chapel in the form of interactive geometrical shapes. Another example is 'Oasis' by Yunsil Hoe from Seoul. By moving the black sand on the desk, moving new borns appear. The interactive dance installation 'Replica', created by Alex Vessels and Jeff Howard in New York, is also believed a processed work. Self-perception should be affected by the new-won awareness of time and images, while watching their installation.
























































Some artists, like Jan Wihlhelm Tulp and Mark McKeague are known for data visualization based on statistics. Tulp, for example, created 'Ghost counties', which depicts the number of (vacant) homes for all the counties for each state. Moreover, Marc McKeague represented traffic on Picadilly Circus with the help of processing called 'City Symphonies'.




Every webpage is written in a language called HTML, which stand for Hypertext Markup Language. Hypertext refers to text containing links in it. Markup Language is a programming language used to make text do more than just “sit” on the page, it can turn into images, links, tablets, lists etc. More precisely, HTML is sort of a skeleton that gives every page a structure. Like any language, it has its own special syntax that must be respected.

CSS (Cascading Style Sheets) can be considered the “skin” or “makeup” that cover the “bones” of HTML. In other words, CSS determines the way an element is represented on a web page.

Codeacademy.com is a fun and simple web page which makes programming really easy. You can start off with the basics and take several tutorials with different difficulty levels. It is ideal for beginners and gives instructions for each step.


























































Data is a value assigned to a thing and refers to information, especially facts or numbers, collected and stored by a computer. Nowadays, data is becoming more and more open and is all around us. Everything we see is processed data. The question, how to represent data, is a challenge for today’s designers. To make data useful, it needs to be structured and interpreted. Data can be split in different kinds of categorizes:

• Quantitative data (data that refers to numbers like prices, sizes)
• Qualitative data (description of colours, texture, everything referring to quality)
• Categorical data
• Discrete data (numerical data, only whole numbers accepted)
• Continuous data (numerical data, all values possible, conitnuous such as shoe sizes for example)

There are 3 ways to find data:

1. Finding already released data from governments, organisations, science
2. Getting hold of more data from official sources
3. Collecting data yourself, on your own or collaboratively

For geographical data, mapping is the most used method to visualize the information. With quantitative data, however, column charts are better suited and for categories analyzed over time, line charts seem to be the perfect choice.





After being introduced to the software Processing, we started off with a few basic assignments like creating a house by coding. First we had to type in the data into Excel and export it as an CSV file. From there you can copy the information to the Processing program. After having typed in all the lines of codes needed, you just need to press the 'play' button to run your coding.



























































































After creating a house, I then played around with different scales and colors and creating an ellipse following the movement of the cursor. (see below)











































































After the example of Emily seen in class, I tried to visualise the top 8 songs I listened to last month by using the Processing program. So I began by developing a chart in excel, than typed in my instructions in Processing and ran the sketch. This is what came out.





























































In addition, I tried to visualise university choices by using bigger and smaller circles, so you see at first glance, which universities are the favourite ones.





























































My last processing sketch was a bit more complex. I wrote down, how many minutes per day I spent doing a certain thing, meaning how many minutes I spent skyping, doing sports, working for university, eating, showering per day. After taking notes on my activities, I visualised them as pie charts in Excel.


























































After processing the data I gathered for a week, I calculated the total of minutes spent per activity and this is the result of my little survey.