Provide guidance to authors of datasets of any scale as to the structuring of their collection data, with the aim of minimizing loss of information or data quality in the case of import to a database. Mirror the current state of knowlegde as the inherent structure of collection data, as far as a consensus can be reached. I think it is agreed that logical data modelling techniques are an indispensable tool for the analysis of complex data such as present in our field. However, truly implementation independent models reach a degree of abstraction which may make them very complicated reading to the avarage system designer, not to speak of the avarage individual creating a dataset. Furthermore, of the examples provided in the References document, non is implementation independent, most of them are based on the relational data model, some even directed to the implementation of a specific database.
Contents metastandard or complex data dictionary.
Metadata is data about data. The concept of a hierarchical decomposition of data items in successively more restricted data elements is intruiging. It allows to quickly pick an choose data element relevant to a defined task at-hand, and a great deal of flexibility as to the delimitation of individual data fields is maintained, because higher hierarchical levels may effectively represent concatenations of atomic data items. It can cover the needs of large-scale databases as well as the needs of small scale databases or datasets set up by individuals. It is the latter category where most of the original data are stored, their incorporation into large scale databases is often made difficult by inprecise structural defintions.