Dirty data

Dirty data, also known as rogue data,[1] are inaccurate, incomplete or inconsistent data, especially in a computer system or database.[2]

Dirty data can contain such mistakes as spelling or punctuation errors, incorrect data associated with a field, incomplete or outdated data, or even data that has been duplicated in the database. They can be cleaned through a process known as data cleansing.[3]

Dirty Data (Social)

Following the definition of Gary T. Marx, Professor Emeritus of MIT, there are four types of data:[4]

  • Nonsecretive and nondiscrediting data:
    • Routinely available information.
  • Secretive and nondiscrediting data:
    • Strategic and fraternal secrets, privacy.
  • Nonscretive and discrediting data:
    • sanction immunity,
    • normative dissensus,
    • selective dissensus,
    • making good on a threat for credibility,
    • discovered dirty data.
  • Secretive and discrediting data: Hidden and dirty data.
gollark: You should probably not be hardcoding sizes.
gollark: Not just "it's like WINDOWS, but for ComputerCraft, and actually not really like Windows as much as just a start menu, desktop and one GUI program".
gollark: They're typically significantly more interesting and creative.
gollark: Copy-pasting this from two months ago:Wild theory on new people constantly wanting to make an OS: they think something like "Oh wow, CC is so unlike Windows! And I have never seen any desktop OS but Windows! I must make it more like Windows so it is more familiar. Clearly nobody else has done this, or it would already be the default, because this is obviously better." Not explicitly/exactly that obviously, but think this might be close to what's going on.
gollark: It uses the CraftOS shell, yes, because I don't like GUIs and this was easier.

See also

References
  1. Spotless version 12 out now
  2. Margaret Chu (2004), "What Are Dirty Data?", Blissful Data, p. 71 et seq, ISBN 9780814407806
  3. Wu, S. (2013), "A review on coarse warranty data and analysis" (PDF), Reliability Engineering and System, 114: 1–11, doi:10.1016/j.ress.2012.12.021
  4. "Notes on the discovery, collection, and assessment of hidden and". web.mit.edu. Retrieved 2017-02-17.


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