In semi structured data model, the information that is normally associated with a schema is contained within the data, which is sometimes called "self-describing". In such database there is no clear separation between the data and the schema, and the degree to which it is structured depends on the application. In some forms of semi structured data there is no separate schema, in others it exists but only places loose constraints on the data. Semi-structured data is naturally modeled in terms of graphs which contain labels which give semantics to its underlying structure. Such databases subsume the modeling power of recent extensions of flat relational databases, to nested databases which allow the nesting of entities, and to object databases which, in addition, allow cyclic references between objects.

Semi structured data has recently emerged as an important topic of study for a variety of reasons. First, there are data sources such as the Web, which we would like to treat as databases but which cannot be constrained by a schema. Second, it may be desirable to have an extremely flexible format for data exchange between disparate databases. Third, even when dealing with structured data, it may be helpful to view it as semi structured for the purposes of browsing.