Folksonomy and Taxonomy

I have been so busy lately that this debate has remained out of my radar. There is a debate currently on the merits of folksonomy and professionally developed taxonomy (or controlled vocabularies) for assigning values to metadata (tagging in the folksonomy parlance). The discussion focuses mainly on the information classification, which indeed is an important part of metadata based search. Many to Many has a post on the positive side which referred to a negative side. I believe there must be more posts on this debate.

My take on the issue is that we should not forget that metadata is only one of the many methods that we can use to find information, including e.g. digital images. See my earlier draft: Meta Meta Meta Data Draft 0.1b - in plain English For example, I do not believe Google has employed an army to tag images found on the web. It is likely to tag the images by the words near the image, or the file name of the image.

My pragmatic approach is still based on "fitness for the purpose". In a digital library where you have an army to classify information against a well established taxonomy. Why forces to use the evolving folksonomy? On the other hand, in evolving domains where developments are rapid and classification is fluid, taxonomy will not have been developed. Other methods should be used. Among the methods, folksonomy is one of them.

Discovery alone is not the best approach either. Without ranking, over thousands of returned results are quite useless. Even with progressive search refinement, still any use of the search result will demand quite an effort to work through a non-ranked list. Ranking of search results is NOT related to classification. Many methods are available too.

I would rather like to broaden the folksonomy verse controlled vocabulary debate to identify typical use pattern and debate on the best approach to meet the needs of "most" uses - leaving the long tail for niche application to fill the demands. Of course, one may choose to be a niche solution provider.