Project Hyperessay II – The Viewer

Building up on my initial concept of using data and links, I feel that the viewer would play a key element in the project – they will be contributing to the project itself by handing certain Facebook data that is already public (friends, connections, checked in) in order to build up a rough relationship map of ADM.

I believe that the relationship of ADM students and professors beyond simply being under the same institution would be an interesting aspect to explore – how many students and professors are actually connected to each other? Are there more common interests besides subject-specific areas? How many people have gone to the same place?

To do this, the viewer must also become an active participant in the project. The network map depends on data given by interested parties – the viewer must be willing to share something for the work to grow.

Given that we’ve only worked with static, defined data, I’ve been pondering as to how the project would be materialized – hopefully something like this website built with Gephi, but with the links being made on-the-fly based on common factors from the data the participants give.

site

Screenshot of a site built with Gephi to visualize social connections

Overall, the project depends entirely upon the participation of viewers in order to build a cohesive map – they play a key element in the building up of the work, in as much as they are viewers of the work. This makes the work a collaborative effort in a way, taking shape depending on participation and input.

Project Hyperessay I: What links us together?

The internet is a wonderfully large, strange, shared space for all of us. Each one of us maintains an online presence in some form – whether it be through social media, forums, media sharing, or online portfolio sites, we all have at least some sort of virtual footprint. Most people give a ton of their data away online, willingly – posting when they leave their homes (not safe), where they go on vacation, what they eat, their opinions on certain events, etc. While for the most part, these are individual experiences and postings, the online platform gives us the opportunity to connect these individuals together.

As previously explored in our past lesson, data visualization gives us an opportunity to explore connections, and create meaning out of it – or use it to create something else entirely. I turn to Lev Manovich’s outlook on the use of data visualization:

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.

-Lev Manovich

Data visualization gives us the opportunity to encompass the vast amount of connections and commonalities we share into something tangible and readable. I feel that it would be a great way to feature something more than what most data visualization tools do, which usually highlight friend connections and common school institutions.

Graph1

Data visualization of my social network, generated by TouchGraph

Graph2

Friend connections generated by FriendWheel

With all the data we make available, I feel that it is possible to collate them together visually and hold a discussion on how we are linked together, individually. Perhaps somehow linking to Instagram, and showing who in your networks post under certain hashtags, or a geo-map showing where you and your friends have been, linking the pictures together over a map. We could also collate Facebook posts based on content (quite ambitious, perhaps) and connect friends based on the type of content they post.

instagram

Mapstagram, which tracks new posts tagged in limited cities across the US

Whilst the data to be visualized is subject to our interest, I feel that data visualization is a great point for us to consider, as it explores the intertwining of our lives while at the same time emphasizing the isolatory and individualistic nature of social media (since they are all “me-centric” rather than “we-centric”.)

Datamatics: Breaking Space Into Visualized Data

Ikeda uses data as a source for sound and visuals, using dynamic CGI to render visualisations and synthesisers to create music. You can see an example in the video above. The data is sourced from hard drive errors and software code, and then run through a stack of filters and processing algorithms to turn it into music and animation that’s not too far off glitch art.

The result is sparse, black-and-white imagery with just the occasional flash of colour, overlaid with high-frequency bleeps and blips and underpinned by droning bass frequencies. You can hear a sample on Soundcloud. Ikeda uses high-framerate video and variable bit-depths to, as the artist puts it on his website, “challenge the thresholds of our perceptions“.

– Duncan Geere, wired.co.uk, 07 April 2011

 

Datamatics is a series of audiovisual works by Ryoji Ikeda, turning space into visual data points flying past our eyes. The work breaks down our perception of space, turning the space into 1s and 0s. It converts our space from a physical plane to something less tangible, more electric. He helps visualize data errors in an artistic manner that is surreal and tangible.

Though the process of data corruption cannot be actually visualized, Datamatics uses such data in creating its vivid imagery and music. In that sense, Datamatics is anti-sublime because it maps something that is nearly intangible into a form that we can decipher.

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.

-Lev Manovich

The generation of imagery and music from a nearly intangible form is reminiscent of Norman McLaren’s work with film – he simply drew what he wanted directly on film, creating fast moving images and futuristic sounding music. While not anti-sublime or data-related, it is interesting to see Datamatics in comparison to his films, such as Synchromy.

 

Ryuji Ikeda’s Datamatics in Ars Electronica 2009

Datamatics blurs the line between the intangible data and the physical space we inhabit, and in that way creates a new sensed space for us to explore, superimposing our physicality with the seemingly nothingness of data. It brings down the formless into form, and forces us to rethink of how we see the world – whether we see objects made of 1s and 0s, or whether we see data as matter.