  Knowledge about data completeness is essentially in data-supported decision
making. In this thesis we present a framework for metadata-based assessment of
database completeness. We discuss how to express information about data
completeness and how to use such information to draw conclusions about the
completeness of query answers. In particular, we introduce formalisms for
stating completeness for parts of relational databases. We then present
techniques for drawing inferences between such statements and statements about
the completeness of query answers, and show how the techniques can be extended
to databases that contain null values. We show that the framework for
relational databases can be transferred to RDF data, and that a similar
framework can also be applied to spatial data. We also discuss how completeness
information can be verified over processes, and introduce a data-aware process
model that allows this verification.
