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For certain database tasks that require great exibility, some people are turning to a new kind of data representation in which the database is not constrained by a schema. Instead, each component of the database carries its own description, which is independent of other components. Systems like ACeDB, which has become very popular with biologists, and the recent Tsimmis proposal for data integration organize data in tree-like structures whose components can be used equally well to represent sets and tuples. What query language is appropriate for such structures? Here we propose a simple language UnQL for querying data organized as a rooted, edge-labeled graph. In this model, relational data may be represented as xed-depth trees, and on such trees UnQL is equivalent to the relational algebra. The novelty of UnQL consists in its programming constructs for arbitrarily deep data and for cyclic structures. While strictly more powerful than query languages with path expressions like XSQL, UnQL can still be eeciently evaluated. We describe new optimization techniques for the deep, or \vertical" dimension of UnQL queries. Furthermore, we show that known optimization techniques for operators on at relations apply to the \horizontal" dimension of UnQL.