DATT 3935

Images used in this GIF were made by E. J. Stanley in 1916. The creator of the GIF is unknown.

[datt3935kaylamacdonald]

Reading Response #4

Last week we had our data art presentations. For my response I will focus on Nathan’s project.

When Nathan first opened the project I was very confused. However, after explaining the ideas behind the project, it became much more clear and interesting to me. I really liked the idea of having an art piece where the viewer explores the piece themselves. This also meshes well with the connection to stars. The piece allows the viewer to explore the piece in a similar way one would explore and make their own constellations when looking at the stars. In relation to this, I would agree with David that panning over the star like squares would’ve been better then scrolling up one line at a time. It’s a little confusing with the two themes and the panning would’ve added to the star like feeling. I also liked Nathan’s suggestion to have this piece projected on a wall all the time. I liked the idea that it’s not an art piece you need to interact give all your attention to but it can be projected in the background and you can explore it at your own pace. Another thing I liked about Nathan’s project is how it is abstract. I liked that it is not clear the reasoning behind the colour of the square and exactly why it’s positioned there. I feel like that added to the star like feeling.

[datt3935kaylamacdonald]

Data Art Project - Global Village Or Self Reflection?

My project focuses in on what we do on the internet. It is often argued that we live in a global village, however most of our internet usage is geared towards ourselves. Sites like Facebook, Google and Twitter use information they’ve gained about you to filter the information they show you. Everyone then subsequently filters that information to fit their own needs. For example, when you’re scrolling down twitter, are you likely to read through every tweet thoroughly or are you likely to scroll through and pay more attention to tweets that connect with your interests? Going through each tweet thoroughly would take much longer and be a bigger strain on our brains. Also, it’s generally fairly obviously to tell when something like an ad pops up on the twitter feed, that you do not want to read it. Therefore, we use our own subconscious filters to wade through all the information. Thus, our internet usage is likely to result in a reflection of ourselves, instead of a reflection of the globe as a whole.

The first portion of my project symbolizes the information overload. The user must then “put on their reading glasses to look at their timeline”. The timeline is made up of roughly 50 tweets from my own personal timeline. I then went through those tweets on twitter and paid close attention to the things I actually look at and the things I skim over. Everything that I skimmed over is blacked out. This gives an idea of how much information we’re really taking in and how much were avoiding. The blacked out Twitter feed also reflects me. You can now take a good guess at who my reals friends are by looking at the similarities between who posted the tweets I looked at most, and what my interests are. The video inside the glasses also represents this kind of self reflection that happens when using sites like Twitter.

Citations:

Roughly 50 tweets from my (Kayla MacDonald’s) Twitter Feed from Nov. 27 at approx. 7pm.

Image citations:

"Index of /Kutuphane/reklamlar/images." Kpssrehber. Accessed November 30, 2015. http://www.kpssrehber.com/Kutuphane/reklamlar/images/.

"Where's the Down Key?" Microsoft. Accessed November 29, 2015. http://answers.microsoft.com/en-us/office/forum/office_2007-excel/wheres-the-down-key/e7eb2a81-ad2b-49cd-b654-634be60fa04d?db=5&auth=1.

[datt3935kaylamacdonald]

Ze Frank Presentation

Citations:

Barnard, Nora. "History of Comedic Vlogging." ...defining Web Video. Accessed November 12, 2015. http://web.colby.edu/am297/history-of-comedic-vlogging/.

"Your Life in Jellybeans." FlowingData. November 27, 2013. Accessed November 12, 2015. https://flowingdata.com/2013/11/27/your-life-in-jellybeans/.

"Ze Frank." BuzzFeed. Accessed November 12, 2015. http://www.buzzfeed.com/zefrank.

"Zefrank." SoundCloud. Accessed November 12, 2015. https://soundcloud.com/zefrank/tracks.

"Ze Frank." Know Your Meme News. Accessed November 12, 2015. http://knowyourmeme.com/memes/people/ze-frank.

"Ze Frank." LinkedIn. Accessed November 12, 2015. https://www.linkedin.com/profile/view?id=AAkAAAACb-IBmwg_UmeEty4ILZFoJcW4JIkuYs4&authType=NAME_SEARCH&authToken=Ev1b&locale=en_US&trk=tyah&trkInfo=clickedVertical:mynetwork,clickedEntityId:159714,authType:NAME_SEARCH,idx:2-1-2,tarId:1447.

Ze's Page. Accessed November 12, 2015. http://www.zefrank.com/.

"Ze Frank." Wikipedia. Accessed November 12, 2015. https://en.wikipedia.org/wiki/Ze_Frank.

"Ze Frank's Star.me Is Like Being In Kindergarten All Over Again." TechCrunch. Accessed November 12, 2015. http://techcrunch.com/2011/02/04/star-me/.

"Whipass :: Goose Extended Mix, by Goose Remixes Ray." Zefrank. Accessed November 12, 2015. https://zefrank.bandcamp.com/track/whipass-goose-extended-mix.

"Ray Hagins (Whoop Somebody Ass)." YouTube. Accessed November 12, 2015. https://www.youtube.com/watch?v=s-F4-FI8A0I&list=PLECB51F45F698FBB2.

"Ze Frank | Search Results." TED.com. Accessed November 12, 2015. http://www.ted.com/search?q=ze frank.

Agger, Michael. "How Ze Frank Became a Web Video Star." Slate. Accessed November 12, 2015. http://www.slate.com/articles/technology/the_browser/2007/03/laptop_celebrity.html.

Presentation PDF:

https://www.scribd.com/doc/289502966/Ze-Frank

Presentation content that is not interactive in pdf:

Sad Cat video -http://www.buzzfeed.com/zefrank/sad-cat-diary#.tuenD3DYJ

Your Time (In Jelly Beans) - http://www.buzzfeed.com/zefrank/the-time-you-have-in-jelly-beans#.wlkQ8g8MW

Ray whipass song - https://www.youtube.com/watch?v=s-F4-FI8A0I&index=1&list=PLECB51F45F698FBB2

Goose Remix - https://zefrank.bandcamp.com/track/whipass-goose-extended-mix

Pain pack - http://www.zefrank.com/pain_pack/

Chillout song - http://www.zefrank.com/chillout/

Chillout voice 1 example - https://soundcloud.com/zefrank/just-breathe-laurie-vocal

Chillout voice 2 example -https://soundcloud.com/zefrank/chill-1

youknowily - http://www.zefrank.com/ily/

[datt3935kaylamacdonald]

Assignment #2

Dataset Citation:

"September 2012 – Teens and Online Privacy." Pew Research Center Internet Science Tech RSS. September 29, 2012. Accessed November 11, 2015. http://www.pewinternet.org/datasets/september-2012-teens-and-online-privacy/.

[datt3935kaylamacdonald]

Reading Response #3

Recently, new media art has turned towards data for both subject and material. Mitchell Whitelaw writes about data art in the article Art Against Information: Case Studies in Data Practice. He starts off by pointing out the differences between information and data. They are closely connected and many seem to use the words interchangeably, however there are differences between the two. Information refers to knowledge gained from manipulated, organized or processed data. Information relates to context and meaning, where data refers to the sheer measurements or numbers. Data doesn’t hold any real meaning until organized and put into context.

Whitelaw then talks about 4 labels data art falls under. These labels are, indexical, abject, material , and anti-content. The indexical data practice is closely related to reality. In this practice data art is created without manipulating the data into different forms and instead representing the data with its original form nearly intact. The abject data practice on the other hand, takes the raw data without context and maps this into another from. The rules or logic around this mapping is not necessarily known but still shows patterns through its overall shape. The material practice also takes the data and maps it to another form, however the logic and mapping of the project are transparent and straightforward revealing structures in the data set. The last label Whitelaw talked about was anti-content. This data practice focuses on taking information, mapping it to data and extracting new information from this data. This practice mirrors the technique used in painting called the artist’s squint. In the artist’s squint, the artist will squint at the object they’re painting to blur the object. They will then paint what they can see with their eyes squinted. This gives the effect of pulling out the important parts of an object and focusing on that instead of the entire object when painting. The same technique is used in the anti-content data practice.

Citation:

Mitchell Whitelaw, "Art Against Information: Case Studies in Data Practice," 2008

[datt3935kaylamacdonald]

Reading Response #2

The Aesthetics of Information Visualization and The Anti-Sublime Ideal in Data Art:

The above articles both look at of data visualization and examine it in terms of art. An important part of data visualization relates to math, sciences, physics, etc. where visualizations are used to increase the speed that one can evaluate the information. With this in mind data visualization art is made so that large incomprehensible data can be put in a format that allows the viewer to analyze and explore the data better.

Generally speaking, as an area of investigation and experimentation, information visualization comprises a set of tools and techniques for distinguishing the “forest” from the “trees,” for literally drawing out the big picture from a myriad of data details. (Sack)

This tilt towards creating art that displays user friendly information contrasts modern art forms. Modern art tends to lean towards sublime messages where data visualizations lean towards anti-sublime.

If Romantic artists thought of certain phenomena and effects as un-represantable, as something which goes beyond the limits of human senses and reason, data visualization artists aim at precisely the opposite: to map such phenomena into a representation whose scale is comparable to the scales of human perception and cognition. (Manovich)

Since, data visualization tend to display more anti-sublime things there are more politics behind how many and what dimensions an artist chooses to display.  Considering the average human only understands 4 dimensions (x,y,z, and time), and artists must choose which dimensions he deems most important. This can dramatically change the perception the users has depending on which dimensions are shown.

Citations Manovich, Lev. "The Anti-Sublime Ideal in Data Art." (2002). Manovich. Web. Stack, Warren. "Aesthetics of Information Visualization." (2011).Web.

[datt3935kaylamacdonald]

Data Visulization

[failisuck-deactivated20151124]

When you’re so intent on swaying public opinion that you completely ignore how charts (and numbers) work. 

This graphic was shown during the Planned Parenthood hearing. There is no y-axis shown, and the arrows imply that abortions are happening at a higher rate than cancer screenings and prevention services. This is completely false. If you look at the numbers, though, (which were too small to be seen by those at the hearing) you can see that the 935,573 cancer screening and prevention services greatly outnumber the 327,000 abortions that were provided, despite their misleading position on the graph. It’s no surprise that the chart was made by “Americans United for Life,” an anti-abortion group. 

Politifact has corrected Rep. Jason Chaffetz’s misleading graph, and theirs is shown below:

Here’s another Politifact graph including the other services that Planned Parenthood provides:

Graphics were from this Politifact article: Chart Shown at Planned Parenthood  Hearing is Misleading and “Ethically Wrong”

[datt3935kaylamacdonald]

Journalism in the Age of Data - Reading Response

The video “Journalism in the Age of Data” explains the growth and development of data visualization. During the video they talk about how data visualization has started to gain popularity. As result, more and more data visualizations are being produced, not all of which are good data visualizations. This had good and bad sides to it. To elaborate, there is a need for more data visualizations as a result of the growing amount of information we have access to, however, inaccurate data visualizations may tarnish the effects that a good data visualization should have. Data visualizations show the user information in an easier format for them to understand. When they look at these visualizations they generally accept what they’re seeing as truthful. If new comers to the trend start to accidentally or purposely produce data visualizations that inaccurately portray the data, than visualizations will lose this concept of truth and instead be looked at with skepticism. Hopefully, the rise in popularity of data visualization actually increases the pressure to keep the data accurate and truthful. In the video they also talked about data visualization’s focus changing to a more fashion related demeanour with it’s popularity growth. I think this also has both ups and downs to it. The downside of the equation is that, a stronger focus on the aesthetics of a visualization leads to a shallower representation of the ideas. A fashion focus can make the pieces harder to read and therefore harder to create deeper meaning and comparisons from. The upside of the new fashion focus is it pulls more audience members in. I think this is great because many people before the “pretty” data visualizations didn't want to take the time to look at and learn more about numbers and graphs laid out in front of them. Now however, users are getting pulled in by the “pretty” looks of the visualization and as a result learning things and making more connections that they may not have before. Even if users are taking in shallower concepts they are still absorbing more than they would have if they didn’t take the time to look at the visualization at all.

[datt3935kaylamacdonald]

Dataset citation for assignment 1

Aamodt, Mike. "Serial Killer Statistics." Serial Killer Information Center. September 6, 2014. Accessed September 23, 2015. http://maamodt.asp.radford.edu/Serial Killer Information Center/Serial Killer Statistics.pdf. 

Click here to view the data.

[datt3935kaylamacdonald]

I stumbled across these GIFs and thought they were pretty interesting. The cheetah GIF was created by Jacob O’Neal and the Flight Videos GIF was created by Eleanur Lutz. These pictures and other interesting GIFs can be found at http://visualoop.com/blog/4093/20-instructive-gif-animations. To see more of Eleanur’s work you can visit her website, http://tabletopwhale.com/index.html. 

[datt3935kaylamacdonald]

Intro

My name is Kayla MacDonald, I’m a third year Digital Media student at Yorku. I spend my spare time at my Crossfit gym and hanging out with my friends and roommates. I grew up in Keswick, ON and moved to Toronto when I started at Yorku.

I’ve chosen to enrol in DATT 3935 to satisfy the requirements I need to graduate and the requirements needed to apply to an internship through the university. I chose DATT 3935 over the other classes I could’ve taken because I generally enjoy working with numbers and thought it would be interesting to take a class that combines that with visuals.

My current knowledge of data visualization consists mostly of things seen in math class and science textbooks, including bar graphs, pie charts and other diagrams used to illustrate the material.

I’ve included a link to an interesting data visualization project that depicts the size of the solar system: http://www.thisiscolossal.com/2015/09/to-scale-the-solar-system/