The initial goal of many metadata efforts was discoverable data but, like many other elements of data management, the metadata landscape has evolved considerably over the last decade to include new use cases and requirements. At the same time, years of emphasizing discovery and minimal metadata requirements have resulted in a culture that accepts that:
- metadata are only for discovery, and
- complete metadata are too complex or difficult for researchers to understand and create.
Evolving the culture past this “data-discovery plateau” requires a multi-faceted approach that addresses multiple use cases, multiple recommendations, metadata in multiple dialects, and limited human and financial resources. The approach we have developed includes web-based tools for understanding and comparing recommendations and dialects, flexible comparisons of completeness of metadata collections (in multiple dialects) with respect to particular recommendations, evaluation of completeness of single metadata records, identification of specific metadata improvement needs and an open forum for sharing information, experiences, and examples.