The integration of data from different sources often
leads to the adoption of schemata that entail a loss of
information in respect of one or more of the data sets
being combined. The coercion of data to conform to
the type of the unified attribute is one of the major
reasons for this information loss. We argue that for
maximal information retention it would be useful to
be able to define attributes over domains capable of
accommodating multiple types, that is, domains that
potentially allow an attribute to take its values from
more than one base type.
Mesodata is a concept that provides an intermediate
conceptual layer between the definition of a relational
structure and that of attribute definition to aid
the specification of complex domain structures within
the database. Mesodata modelling techniques involve
the use of data types and operations for common data
structures defined in the mesodata layer to facilitate
accurate modelling of complex data domains, so that
any commonality between similar domains used for
different purposes can be exploited.
This paper shows how the mesodata concept can
be extended to facilitate the creation of domains defined
over multiple base types, and also allow the
same set of base values to be used for domains with
different semantics. Using an example domain containing
values representing three different types of
incomplete knowledge about the data item (coarse
granularity, vague terms, or intervals) we show how
operations and data structures for types already existing
within the mesodata can simplify the task of
developing a new intelligent domain.Sydney, NS
