Quality is a decision - a decision based on a desired outcome. When it comes to data, GIS data in particular, it is as the saying goes - garbage in – garbage out. As project pace picks up and milestones turn into deadlines, it is easy to overlook the relevance of data quality as a front line mechanism in assuring purposeful data. The collection of data must have sound intention - requirements that would allow it to provide information, disseminate knowledge, and propagate wisdom, albeit fulfill its original purpose.
To chase or control quality of data after the fact, reminds me of squeezing out toothpaste. If squeezed too hard, too much comes out and with no way of getting it back into the tube, you must find a way to use the extra. With storage being non-issue these days, the exorbitant quantity of data being stored is likened to the toothpaste scenario. Control must be established from the start to control the superfluous flow of data. Check points need to be set to alleviate damage control down the road. Once data moves from one point to the next, it must exist in a state in accordance with its intended usage. The data must be complete, valid, business specific, accurate, and relevant. The more refined the approach to quality, the assurance of a better product.
