The
advantages of meta-data driven software generation are:
Data documentation: The data together with their statistics and
important features for data mining (e.g., presence of null values) are
well documented. This extends the meta-data as are usual in relational
databases.
Case documentation: The chain of preprocessing operators including
all parameter settings is documented, as well. This makes a case reproducable.
In contrast, the current state of documentation is most often the memory
of the particular scientist who developed the case.
Abstraction: Meta-data are given at different levels of abstraction,
a conceptual (abstract) and a relational (executable) level. The same
case at the conceptual level can be mapped on several different cases
at the relational level. This makes an abstract case re-usable.
Ease of case adaptation: In order to run a given sequence of operators
on a new database, only the relational meta-data and their mapping on
the conceptual meta-data has to be written.
