It can be difficult to maintain the fitness of a metadata catalog. Catalogs are increasingly diverse and rapidly growing in size. Without good metadata it is difficult for users to discover datasets likely to be useful, but more importantly good metadata is essential for converting that dataset into information so it can be transformed into knowledge and understood and used in new and novel ways. How can curators ensure the catalog’s ability to meet the different needs of the users of data? How can catalogers quickly evaluate the likelihood that a record in the catalog will contain all of the metadata needed by a potential user of any resource described, and which collections need specific types of improvement? A visualization that can provide these insights is needed that can impart the shape of the catalog’s fitness for meeting different user’s information needs.