This is many months old, but I thought I should post this as its a very early attempt at making a web application in Node.js as part of my Dynamic Web class. The final for Dynamic Web will be posted in a week!
The inspiration for my final is an eery and beautiful project I discovered recently, called 12:31, which uses hi-res scans of the entire human body to create these ghostly portraits:
I began doing research on the source images, which were created by the National Library of Medicine’s Visible Human Project, and was just given permission by the NLM to access their 100GB+ dataset! A lower res movie of the black and white scans is below:
THE CENTRAL QUESTION
Of course, the Visible Human scans are themselves data visualization, but after examining the images, I think that more can be gleaned with the addition of a sonic component. Moving through the body has a very rhythmic and almost mesmerizing quality to it that gives it potential in the medium of sound/music. My central question is “How can we create a different perspective on the body by hearing its structure and features, instead of just seeing it?”Analysis of the images for symmetry, prominent features (blob detection) and overall composition (color analysis of pixels) will hopefully lead to a sonification that best represents the data’s character.
I’m hoping to do my main analysis in Processing, potentially using the CV libraries TSPS or openCV, and then build a small website that houses the representation in the form of a playable/scrubbable image sequence, with the sound accompanying it. I’ve also had some wackier ideas that I need to develop further, but the analysis phase will probably remain similar.
Our assignment for this week’s class was to represent a very large dataset of hotel information– around 500,000 datapoints (!), including name, latitude and longitude, ratings, etc. The first part of the assignment was to create six mini world maps, one map for each star rating (0-5). We are also tasked to find the northernmost hotel according to the data, and the most remote hotel.
The most northern hotel wasn’t too hard to find, as I created a variable that held the most northern (x,y) point, which was constantly being overwritten as I looped through each hotel, replacing the current most northern hotel with any new hotel that was even farther north. The most northern hotel is the Radisson Blu Polar Hotel, in Norway.
Alas, I wasn’t able to crack the most remote! My plan, which I think would work, was to find the nearest neighbor for each hotel, and then sort the hotels by that distance (i.e. the hotel whose nearest neighbor is farther away than any other hotel’s nearest neighbor). I had some trouble accomplishing this plan (I think) because of the way I structured my data object and ArrayList.
Sorry for the grainy photos! I’m using Rhino 4 on the Windows side now, so no more screenshots.
Sam and I made a lot of headway on our project concept, and I’m super excited about where we’re headed. We’ve significantly honed in on a topic within the prison/education world to focus on the school to prison pipeline. Its a fascinating and sad systemic problem in this country, where children’s bad behavior in school has been criminalized and problematized to the point where delinquent acts that would have been taken care of “in-house” are now being treated as criminal acts, leading to suspensions, expulsion and real jail time. Children as young as 7 years old are being arrested (!), teenagers who are 15, 16, 17 years old are being slammed with adult prison time. The data shows that even a string of suspensions drastically increases drop-out rates and often foreshadows a future in the prison-industrial complex.
We wanted to use familiar objects that children might use in school (books, gym sneakers, binders, keepsakes) to evoke the damage to a child’s future that occurs when we criminalize non-criminal behavior. 3D printed and laster cut data with be grafted onto or attached to actual school supplies and items and will be arranged in a locker, just like you might see in an elementary or high school.
The last image in the gallery is a quick Processing sketch, randomly scattering data, which makes it easier to find interesting surprises. The size of the circles are the number of arrests, according to different charges. Non-violent crimes are most common, and drug abuse (not dealing) charges and “all other charges” top the list. Serious violent crimes such as aggravated assault represent a small percentage of the total.
For our first assignment in Jer Thorp’s Data Rep class, I explored data on marriage rates in the UK, from 1862-2009. I waffled between this topic and another data set, but went with marriage rates because its not a large set but it has a lot of interesting details.
Looking at total marriages per year is interesting because you can surmise a number of major events in the countries history. Both World Wars show a spike in marriages at its outset (tying the knot before soldiers we shipped off) and then steep declines as the war continues. In more contemporary times, we can see marriage rates dropping, as well as the overall population gap between men and women narrowing, by looking at the rates of married men and women per 1,000 unmarried.
For my 3 x 3 animal analysis, I chose to focus on German Shepherd’s. While its a particular type of dog, I think it was helpful to narrow the focus, and in the end it made the trajectory of the dog’s image in culture even more interesting to me.
The first instance of the German Shepherd that I’ll focus on is the Hollywood animal-star, Rin Tin Tin. Rin Tin Tin was literally german–rescued by an American soldier named Lee Duncan in WWI–and then vaulted into stardom in the 1920′s after his owner realized his talent for jumping and doing tricks.
Like other dog movie stars, Rin Tin Tin was often cast as a hybrid wolf-dog, fighting bad-guys but also fighting or resisting his “wildness.” He chose to be a protector of humans and a member of our community instead of his own. Rin Tin Tin is a romantic figure and and could be read as an animistic representation of the human-animal bond. Interestingly, Rin Tin Tin’s heroism on screen paved the way for German Shepherds to be employed in the WWII effort.
While the image of the German Shepherd as searcher/rescuer is one I cherished as a kid, it now seems relevant to the idea of objectification, since German Shepherds were first bred in 1899 for their utility to human activity. Their very existence is predicated on human utility.
The journalistic discourse of the first image suggests that we are witnessing the dog “just doing its job,” with little fanfare. The dog is like the human rescue worker: sacrificing, brave, humble. However, we still still the noble/romantic notion peeking through the journalistic discourse in the second image taken after the 9/11 attacks. It trades more in propaganda as a discourse, but the German Shepherds heroism still emanates from its usefulness to us.
The last set of images depart from the romantic theme and instead complicate the objectification of the animal. Here we see the dog as fear-tool, a symbol of power. We can graft pride onto the search/rescuer dog as an object of utility, but in these images we’ve bred a monster, an extension of human violence and authority.
The dog’s heroic qualities for which it was bred (physical strength, obedience), are now the weapon, an object of fear. The discourse of the Abu Ghraib image, for instance, “knows” this: grainy and detached, it suggests a scene we were not meant to see with subjects who did not expect to be revealed.