Dear all, After 16 days of publishing Grass&Green, a specific tool for QA of data classification, we got the following contributions.
Thanks for all contributors, however, we still have 1000's of entities needed to be checked. I could describe simply how does it work?
We have the following assumptions:
Similar entities should be classified consistently, at least within the same country. For example, In Germany, what people know about "park", as a place for recreation and amusement, doing sport, grilling, pinking, ..etc. Thus, the one can not called a small piece of grass entity in front or backyard of his home as "park". It is inconsistency.
OSM in lots of cities (e.g., urban cities) has a good and acceptable quality.
Hence, we extract the characteristics that describe specific grass-related classes like: forest, meadow, park, garden, and grass. Afterwards, we develop a recommendation system (Grass&Green) for that classes.
The aim of the tool is to improve/enrich the data classification quality of these features. We just have a start and test on Germany DataSet, however, the entire world would be provided in the next phases. So far, contributors confirm our recommendations with 90% full/partial agreement. That's sounds good.
Best, Ahmed Loai Ali