Q1. Given the Wikipedia definitions on data and information, what is your own take on this and specifically what is the difference between data and information?
The main difference between data and information is that data is the unprocessed version of information. First, data is gathered, giving statistics, facts, variables, and more. Information comes after. It is processed data. Information is data that has been processed by being put to use. It is almost like data has no significance in research until it is processed and turned into useful information.
Q2. From the Manovich reading, what is the difference between visualization and mapping?
From my understanding, the difference between visualization and mapping is that visualization is something you cannot see exactly. You cannot come up with an exact image for it, but you can create something that resembles it to make some sort of symbolic representation. It is more limited and can be used for things like data. These are more graph and chart visuals. In short terms, it is data that is turned into an image. Mapping is more of creating connections between different types of data to create something new. An example may be turning sounds into images, like in Audacity. You can upload a photo and play with the waves that are inputted to create glitches on the original photo.
Q3. When Manovich states that visualization is the anti-sublime art what is he referring to? Do you agree with this notion?
This means that any amount of data can be turned into some sort of thing, like a graph or table, and be physically visualized. He says he gets emotionally moved by things like this, but this concept is confusing to me. Yes, it is cool that data can be turned into a kind of art, but it is not my cup of tea. To him, it is taking data or information that can be perceived as something we can actually look at. If sublime art is to produce the strongest emotion possible, then yes, visualization is anti-sublime to me because it evokes no emotion from me unless the information is meaningful to my life.
Q4. Group take home assignment: You will be assigned to a group, each person in the group is in charge of 1 of 6 artists. Watch the video and then write a paragraph summarizing the artist, on what they showed in their presentation, and the type of art they make. Elaborate on their specific interests in data, language and methods of visualization.
Jennifer Daniel works at an engineering company making visual works. She started off the presentation with a slide show talking about how people communicate on the internet, or online vocabulary. We use words, emoticons, emojis, and little stickers. Emojis were created in Japan. They were then produced into unicode, which says what the characters are and what they mean. Emojis are identified by their image and their unicode. There are so many different types of emojis, found on IOS, Android, Twitter, FaceBook, Samsung, Microsoft, and more. Depending on these different softwares, we also see how emojis differ. You could even interpret these with completely different meanings. Emojis can even be combined to say different things. Emotions and emoticons are important factors in how we communicate with each other, and how we want to portray ourselves. Fonts are also identified through unicode. Daniel’s also goes into how illustration does not limit one in how they want to portray themselves. It allows them to define themselves. She has worked on a lot of apps, like the designs of them. She recently worked on a project where on an app, you take a selfie, and it creates custom stickers of different types of reactions. Customizable emoticons allow people to portray themselves how they see themselves, how they want to be portrayed by others, or even create another persona. She states that large data sets are used to describe a multitude of people, which is very true. For many customizable emoticon softwares, there is a limited amount of options for facial features. Apps cannot get every single feature in the world, so data is compiled to create a middle ground for all these similar features. Only basing things off of data is not a pathway to creativity and learning. According to Daniel, if we only use data, all these things become limited. The bias in computer algorithms is not the only reflection of the world around us. We define the language created by these algorithms. We give them their meaning, even changing their existing meanings when we communicate.
Q5. For the artist video presentations 1 thru 6, get together as a group and summarize in your own words what each artist is talking about in their presentation.Then as a group characterize (tag) each one of the artists using the general categories below: You can attach multiple categories for each speaker. For each artist you covered in your group provide a One sentence summary of their work and which category(s), that make sense.
A. Crowd-Sourcing
Jer Thorp is a data artist that makes use of big data like crowd-sourcing to portrait his works by transferring those data into symbols and images that people can interact with and learn from.
B. Data as Process and Exploration
C. Data as Portraiture:
Daniel’s work also fits into data portraiture. Her recent project featured an app where you take a selfie, and a custom sticker pack is created, turning your selfie into many illustrations, allowing you to show different emotions. You become your own emoji.
Jer Thorp is a data artist that makes use of big data like crowd-sourcing to portrait his works by transferring those data into symbols and images that people can interact with and learn from.
D. Constructing Identity:
Jennifer Daniel’s presentation was about the use of emoticons/emojis and how we use them to communicate, portray ourselves the way we want to be seen, or even create our identity through these small images.
E. Self Surveillance
F. Data as Symbols vs Images
I would categorize Stefanie Posavec as a “Data as Symbols vs Images” artist. This is, because she has more emphasis on the visual and using symbols in her artwork.
Jer Thorp is a data artist that makes use of big data like crowd-sourcing to portrait his works by transferring those data into symbols and images that people can interact with and learn from.
G. Data as Interface
H. Software as Platforms and Virtual Communities
I. Creating Data Narratives