Adding structure to unstructured data

We develop a new schema for unstructured data. Traditional schemas resemble the type systems of programming languages. For unstructured data, however, the underlying type may be much less constrained and hence an alternative way of expressing constraints on the data is needed. Here, we propose that both data and schema be represented as edge-labeled graphs. We develop notions of conformance between a graph database and a graph schema and show that there is a natural and efficiently computable ordering on graph schemas. We then examine certain subclasses of schemas and show that schemas are closed under query applications. Finally, we discuss how they may be used in query decomposition and optimization.