Schema Evolution publication categorizer

We briefly motivate and present a new online bibliography on schema evolution, an area which has recently gained much interest in both research and practice.

One of the fundamental aspects of information and database systems is that they change. Moreover, in so doing they evolve, although the manner and quality of this evolution is highly dependent on the mechanisms in place to handle it. While changes in data are handled well, changes in other aspects, such as structure, rules, constraints, the model, etc., are handled to varying levels of sophistication and completeness. In order to study this in more detail a workshop on Evolution and Change in Data Management was held in Paris in November 1999.

We describe examples of problems of semantic heterogeneity in databases due to “domain evolution”, as it occurs in both single- and multidatabase systems. These problems occur when the semantics of values of a particular domain change over time in ways that are not amenable to applying simple mappings between “old” and “new” values. The paper also proposes facilities and strategies for solving such problems.

Time is a pervasive dimension of reality as everything evolves as time elapses. Information systems and applications at least mirror, and often have to capture, the time-varying and evolutionary nature of the phenomena they model and the activities they support. This aspect has been acknowledged and long studied in the field of temporal databases but it truly applies also to the World Wide Web, although it has not seemingly considered as a primary issue yet.

The incorporation of a knowledge of time within database systems allows for temporally related information to be modelled more naturally and consistently. Adding this support to the metadatabase further enhances its semantic capability and allows elaborate interrogation of data. This paper presents SQL/SE, an SQL extension capable of handling schema evolution in relational database systems.

We argue for avoiding database reorganizations due to schema modification in object-oriented systems, since these are expensive operations and they conflict with reusing existing software components. We show that data independence, which is a neglected concept in object databases, helps to avoid reorganizations in case of capacity preserving and reducing schema transformations. We informally present a couple of examples to illustrate the idea of a schema transformation methodology that avoids database reorganization.

Schema Evolution is the ability of a database system to respond to changes in the real world by allowing the schema to evolve. In many systems this property also implies a retaining of past states of the schema. This latter property is necessary if data recorded during the lifetime of one version of the schema is not to be made obsolete as the schema changes. This annotated bibliography investigates current published research with respect to the handling of changing schemas in database systems.