Difference between revisions of "Case Studies/Evaluation"

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Revision as of 19:02, 24 August 2010

It's important for Creative Commons to be able to talk about the impact that our licenses have on the web. Part of this involves collecting use cases from different domains and aggregating some useful metrics. The Case Studies database aims to enable that in addition to providing a way for our community to search and discover interesting uses. But in order for a database like this to be useful, it has to have good solid information.

Evaluation Guide

There are only two axes for evaluating a Case Study on this wiki: Quality and Importance.

Quality

  • Quality should be re-assessed following any substantial edits to a Case Study.
Class Criteria Suggested Edits Examples
A-Class
  • Contains a concise and complete description of the use in well-written prose.
  • Explains the novelty or importance of the use-case.
  • Has complete information, including: an accompanying image with attribution information, quote, short description, and licensing metadata.
  • Would be worthy of being featured elsewhere on the web.
  • No edits should be necessary unless new information becomes available.
  • Example
B-Class
  • Contains good, complete descriptions of the use.
  • Has an image and short description, but might be missing one or two data fields.
  • May need small improvements writing style, gammar, spelling, etc.
  • Fill in missing or incomplete metadata.
  • Fix any minor issues with writing style.
C-Class
  • Contains an adequate description (both short and full) of the use.
  • Some missing image, quote, or metadata.
  • May contain unclear language or obviously incorrect grammar.
  • Fill in missing or incomplete metadata, description, image, quote, etc.
  • Improve prose of the Case Study. The Wikipedia Manual of Style is a good guide.
Start
  • Has the beginnings of a descriptions of the use.
  • Substantial information missing, such as a short description, image, or metadata.
Stub
  • Has no description.
  • Missing large chunks of data.

Importance

Importance Criteria Examples
High
  • Example
Medium
Low

Needs Evaluation

Importance
Quality High Medium Low Not evaluated
A-Class
B-Class
C-Class
Start
Stub
Not evaluated
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