1. The GSIM Statistical Classifications Model is based upon the Neuchâtel terminology model for classification database object types and their attributes v2.1. It was developed by a group of 19 members from 13 different national and international organisations in an endeavour to arrive at a common language and a common perception of the structure of statistical classifications and the links between them. The GSIM Statistical Classifications Model is both a terminology and a conceptual model. It defines the key concepts that are relevant to structuring Statistical Classification metadata and provides the conceptual framework for the development of a Statistical Classification management system.
2. The model has a two level structure, consisting at the first level of the object types (e.g. Statistical Classification, Classification Item), and, on the second level, the attributes associated with each object type. Both object types and their attributes are defined by a textual description. Since the model belongs to the semantic and conceptual sphere of metadata, it does not include object types and attributes which are related solely to the technical aspects of Statistical Classification management. The conceptual model is generally applicable and not dependent on IT software and platforms. It may be used in any context where structured information on Statistical Classifications is required. A simplified object graph gives an overview of the main object types and relationships in the conceptual model.