The Data Cycle

[John Chernega]

The Data Cycle

 

The data cycle used to be labeled with “Resource Alignment,” “Process and Synthesis,” “Interpretation” and “Problem Application”. [Citation needed] New proposals were adapted in late 2016 to match labels for the precipitation cycle. [Citation needed]

 

Gamer Aaron Gray was the first to identify data flurries using an augmented reality game on his cell phone in October 2016, but many others reported it soon after. [Citation needed] Gray theorized that data was being cycled as data in the Cloud hit its upper limits.

 

When data saved to the Cloud (i.e. evapped) surpasses storage limits, the Cloud undergoes a purging process (i.e. going nimbus). Purged data is returned to any device that can receive it, with varying results. During the purging process, no data can be transferred to or from the Internet [Citation needed]

 

Effects of Data Flurries

 

Assessment of data flurries is incomplete, but systems deteriorate from the excess data. Observers have noticed several effects, including:

 

·      Communication disruption

·      Electrical brownouts

·      Limited visibility in screen-enabled devices

·      Inhibition of growth in data trees

·      Shutdown of activity in plants and manufacturing centers

·      Loss of traction in Internet-enabled vehicles

·      Massive interference blocking physical roadway access

 

Gray theorizes that excess interference can be removed with paramagnetic low-omnidirectional waves (i.e. PLOWs) that delete data entirely. This technique has limits, however and would not be effective in data whiteouts. [Citation needed]

 

During one data flurry, observers noted children piecing together pixels on their tablets to make crude, salacious images called datamen. [Citation needed]

 

 

Effects of Data Whiteouts

 

According to Gray’s hypothesis, a sufficient amount of data sent to the Cloud will result in a whiteout, leaving all datapoints disconnected, a sea of random noise, virtually isolating us all from one another. This could portend global catastrophe.

 

[Citation needed]

 

ERROR UNABLE TO CONNECT

[Jeremy Hight]

Data Squalls

Information has been seen to pulse in human behavioristic algorithms

The injection of a flawed headline from up to ten years ago  or a poisoned rhetoric within an easily

digestible link or meme  is a semiotic trojan horse that opens viral misinformation rhizomatically.

Data Hail

Recent studies at MIT  and Harvard have found that 70 percent of shared links contain factual errors or misinformation.

A  Carnegie Melon study in 2015 found that at any time 74 percent of tweets were by bots.

The dimensionality of the nexus of both data results when graphed in ar  finds a similar formalistic geomery.  

The  injection of rising and falling perceived paths in posts, likes and the nueral firing when one gets a like (akin to a pleasure storm synaptically)

is akin to the multiple trajectories of hail in air currents and the eventual false result of a simple short fall.

Data vorticity

Cybernetic flow study finds a clear analog between the interplay of high and low pressure and the life cycle of memes and news cycles in social media. 

Roland Barthes spoke of the  death spiral in language   born within completion and how it comes from within a text to its "skin'.   Text is convective,

narrativization of above theory=

Mark and Rob  watched the storm begin to form over the desert.  Mark was overjoyed at the new rains to soon fall.  Rob saw the same cloud in the same moment and mourned its death, its breath to fall across sands and thin out into later afternoon and away.   Someone a town away wrote a blog post about the storm being sure to flood and it went viral even as the storm never reached a soul and made no flood at all.