Tag Archive: representation


I chose to focus on Manovich’s concepts for my application example, and I chose the 3 I feel most relevant to modern new media.  I have a few examples of media which I feel exemplify the readings.

Modularity

 

 

Numerical Representation

I chose to show numerical representation by showing a low quality vs. a high quality song from Youtube.  The Low quality song uses much less bits to record the song than does the high quality rip

http://www.youtube.com/watch?v=Rb6N71RP-6M

http://www.youtube.com/watch?v=-nqRkAsZumc&ob=av2e

 

 

Transcoding

 

I would lastly like to focus on the idea of transcoding.  Transcoding how various forms of media become “cross-platform”  i.e. they work on various operating systems.  I chose the example of Angry Birds, which originally released on iOS, but has since been ported to Android, the web in the form of a flash game, and now onto desktops, both PC and Mac.

http://www.rovio.com/index.php?page=angry-birds

 

Thanks!

 

 

 

 

 

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Manovich – Numerical Representation

The concept of numerical representation that Manovich presents in this portion of the reading describes all “new media objects” as being digitally coded one way or another, i.e. they can be represented with numbers. There are two important ideas that arise from such a statement, and they are as follows:

  1. Media objects can be described mathematically. Vector imagery, for instance, uses mathematical functions to describe shapes, creating pixel perfect representations of that shape at any resolution.
  2. These media objects can be altered using other algorithms to perform various manipulative tasks. An example of this is shown in the fact that digital photos can be easily improved by pressing the button that changes its brightness and contrast, and this button performs an algorithmic calculation to change the mathematical data contained within the photo.

Manovich then details the process of converting old media into new media objects. While many common terms are given, the one that appears to be of the utmost importance is the concept of changing continuous data into discrete data. He defines continuous data as “the axis or dimension that is measured has no apparent indivisible unit from which it is composed.” Put another way, old analog photographs are just that: one photograph. There is no smaller unit that it can be broken into. New media objects are composed of discrete data, however, which means that the information is defined as a collection of distinct units. A digital photograph is composed of a certain number of pixels, for instance. These pixels hold a quantifiable value that determines its color. Images are not the only thing that adheres to the principle of discrete data; all new media objects are composed of smaller, quantifiable units of one form or another.

Another important idea Manovich expresses revolves around standardization. Once a new media object is introduced, the type of information carried within it can be standardized such that future objects of a similar nature have the same type of discrete data. All digital images are composed of pixels, and as such, digital viewing devices must be able to display pixels. Going one step further, these media objects can be easily broken down into their discrete data in order to produce an identical copy. Every time you use the copy/paste functions on your computer, you are adhering to this principle.