Without context, answers, facts and datum are meaningless. “The ultimate answer to life, the universe and everything” is undeniably 42, however, without the question, lost in an unfortunate galactic construction project, it’s useless.

Wikipedia is an awesome collection of facts, some even with context but, there are many areas, despite the best efforts of the contributors, that lack context. For example, Vincent Van Gogh has a wonderful entry detailing much of his life and explaining the inspirations of much of his works. However, a single link to the post-impressionism article and a few brief mentions of his contemporaries praise and admonitions provide context to his work. This is not a fault with the user driven model, but instead of the toolset. The unstructured nature of a Wiki doesn’t lend itself to comparative analysis – which is of course just one way to provide context to information.

Quantitative information alone is of course insufficient. What if we were to measure the sum of all works by Van Gogh. What measure would we use mass, dimension, net worth – a convoluted formula of all of the above? I am sure the answer would be 42. It’s absurd to compare everything using quantity alone. Qualitative analysis is a critical component in all evaluations. In this area Wikipedia’s model excels. Because the work is living, it can reflect the current thinking on a topic and through the edit history give us context of how perceptions have changed. Unfortunately, it still requires human beings to understand the changes and to provide the perspective – perhaps some graduate student is working on an automated system to solve this problem as their final thesis.

But if we leave the world of art and move back towards less abstract concepts that are easier to quantify, wikipedia fails. The inability to compare and contrast two articles of similar types, such as corporations leaves Wikipedia lacking. Consider Dell and HP. Both are publicly traded companies, both have Wikipedia entries and both have massive amounts of qualitative and quantitative data available about them. To look at the two companies side by side, we have to look beyond the Wiki walls and move to a more data oriented set of information. Google for example does a great job of comparing the corporate stock prices and a whole host of other providers give different toolsets for interacting with the publicly available financial data.

I think there should be a world where these two universes collide, empowering the public to contribute to the qualitative components of data sets in a wiki model, and also have comparative tools that act on the quantitative data.