Large Data Visualization - LeFreq/Singularity GitHub Wiki

We got it. Large data can be visualized with log4(n), hand-inputted categories (n data, single application) or at most log2(n) -- a multi-purpose OS like this one.

Once the categorizations are done, then it is merged into the pre-existing categories and now viewable through the lens of the ThreeDimensionalVisualizationModel.

Some visualizations ideas here...

Network management (inspired from the Matrix):

  • a character cell for each node on the network.
  • cell blinks on with traffic
  • cell (ascii) character encodes type of node (printer, windows 95, linux 2, etc...)
  • cell color says traffic type
  • cell position related to IP assignment OR geographic position
  • blinking cell for problem node: requesting management
  • sysadmin can "zoom" onto cell and see histograms of a particular node
    • different traffic stats (different network traffic NetBios, IP, etc.)
    • different types of traffic (printer jobs, port 80, port 23, etc.)
    • rings (like below) coudl show present traffic and rates
      • distance from center dependent on how many hops to origin/correspondent
      • length of ring is duty cycle of traffic (%age in a given second, minute)
      • direction of ring rotation is input vs. output
      • several categories and ring groups: dependent on layer 2 protocols (assuming all ethernet, but could break it down into layer 1 protocols: wireless vs. wired traffic)
      • color of ring is traffic type in a given category


Process visualization (inspired from Star Wars and Atom IDE):

    

  • User ID in center
    • 

  • rings of apps
    • 

  • different users have different rings
    • 

  • thickness of ring: initial memory size (until user given control)
    • 

  • space between rings could be related to time between apps initial execution.
    • 

  • speed of rings rotation, tells how much CPU time is used.
    • 

  • rotation direction is input bound (and output to disk) vs. (visual) output bound *OR* starting up vs. closing down
    • 

  • composition dependent on memory usage
    • 

  • color of ring is app type
    • 

  • color of user ID is type of user (student, professor, business office, etc.)
    • 

  • ID blinks when problem occurs (idle time too long, security triggers, etc.)
    • 

  • position of rings can be related to TYPE of user or geolocation or login time
    • 

  • system processes can have simple line with %ages or bar graph (no animation) OR switch to SYSTEM view and all process get shown.
    • 

  • black background. core processes have subtle colors deep in this darkness.
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