Evaluation Domains/List of Evaluation Domains

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The purpose here is to create a Data Structure

  • Encapsulation - when common patterns are grouped together under a single name and then parameterized, in order to achieve a higher-level understanding of that pattern.
    • For example an operation requires two source values and writes the product of those two values to a given destination. The operation is parameterized by both the two sources and the single destination.
  • Abstraction- a mechanism to hide the implementation details of an abstraction away from the users of the abstraction.
    • For example, when we multiply numbers, we don't necessarily want to see the technique actually used by the processor, we just need to know its properties." [1]
  • node a container for a value that also has a pointer to the "next" node (which could be "null"
    • Value
    • Next
  • Chain - A string of nodes


The technique used in obtaining some data from other data would be part of the metadata ("Data about data") for a given.

First, we can think of spreadsheets. However, imagine that you can right-click on any given spreadsheet cell, and see links to more cells and algorithms and sheets


We start with three sections:


  1. Disciplines
  2. Approaches
  3. Evaluands

Within those, we have

  1. Sub-Disciplines
    1. Categories of Evaluative Process
      1. Perceptual / Intuitive (Tag: Process)
      2. Inferential / Scientific (Tag: Process)
      3. Holistic v. Analytic (Tag: Descriptive)
      4. Component / Dimensional
  2. Approaches
  3. Evaluands


Expand that further, and we have:

  1. Sub-Disciplines
    1. Categories of Evaluative Process
      1. Perceptual / Intuitive (Tag: Process)
        1. Perceptual <- Implies use of Sensory Organs
        2. Intuition <- Doesn’t imply use of sensory organs.
          1. Memory of Perceptions
          2. Heuristic Processes
          3. Conscious Logical Processes
      2. Inferential / Scientific (Tag: Process)
        1. Inferential <- Formalized
          1. Statistical
          2. Non-Statistical
          3. Formalized
        2. Scientific <- If it’s scientific its either inferential, or we would have to accept that trained intuition.
        3. Trained Intuition <- Intuition developed by comparison to baselines
          1. According to the
      3. Holistic v. Analytic (Tag: Descriptive)
        1. Holistic:
          1. Dimensional
        2. Analytic:
          1. Component
          2. Dimensional
  2. Approaches
  3. Evaluands


  1. http://en.wikibooks.org/wiki/Data_Structures/Introduction Definitions of "Abstraction" and "Encapsulation"