DataGuides are concise and accurate summaries of semistructured
databases, enabling schema exploration and improving query processing.
Unfortunately, DataGuides can be very expensive to compute, especially
for large, cyclic databases. For many DataGuide uses, an
``approximate'' summary of the database's structure can be beneficial
yet much cheaper to compute.  We summarize several uses of DataGuides
and define Approximate DataGuides (ADGs), which relax certain aspects
of the DataGuide definition. An ADG allows some inaccuracy yet retains
properties that make it useful in numerous situations.  The core of
the paper presents two general approaches for building ADGs,
describing algorithms and experimental results.