Metadata modelling and management

Database engineeering addresses domains such as database exploitation, database design, database reverse engineering or database evolution. A database is described through a hierarchy of schemas, each of them expressed in a data (or information) model. A large part of database engineering resort to schema manipulation, where data structures are built, analyzed, evaluated, transformed and used to produced various artefacts such as other schemas, DML and DDL code. The quality and the effectiveness of these schema manipulation processes depend on the availability of appropriate data models. Hence the importance of model development activities (Database Models).

A data model states a definite way to view data but, to be complete, it must be accompanied by languages that tell how to interact with the contents of database, that is, how to manipulate these data. Sometimes, such language takes the form of an API (application program interface) that also defines the technical detail of these interactions (Database languages).

The design and evaluation of models require a means to describe them in a general way and to reason about them (for example, how the Entity-relationship model compares with UML class diagrams?) This is the concern of metamodelling, that proposes models to reason about models, and that are, for that, metamodels (Metamodelling).

This chapter describes the contribution of the LIBD to the development of database models, database languages and API’s and metamodels.

Keywords

database models, metamodelling, database languages, API, object-relational mapping, CASE tool

Contributing projects

• DB-MAIN (Database Engineering)
• e-Health (Data interoperability through an e-Health platform)
• Gisele (model base for clinical pathway)

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