Schema Evolution publication categorizer

Research has investigated mappings among data sources under two perspectives. On one side, there are studies of practical tools for schema mapping generation; these focus on algorithms to generate mappings based on visual specifications provided by users. On the other side, we have theoretical researches about data exchange. These study how to generate a solution -- i.e., a target instance -- given a set of mappings usually specified as tuple generating dependencies.

Many data integration solutions in the market today include tools for schema mapping, to help users visually relate elements of different schemas. Schema elements are connected with lines, which are interpreted as mappings, i.e. high-level logical expressions capturing the relationship between source and target data-sets; these are compiled into queries and programs that convert source-side data instances into target-side instances.

In this paper we study the problem of schema exchange, a
natural extension of the data exchange problem to an intensional level.
To this end, we first introduce the notion of schema template, a tool for
the representation of a class of schemas sharing the same structure. We
then define the schema exchange notion as the problem of (i) taking a
schema that matches a source template, and (ii) generating a new schema
for a target template, on the basis of a set of dependencies defined over
the two templates. This framework allows the definition, once for all,

Data exchange is the process of converting an instance of one schema into an instance of a different schema according to a given specification. Recent data exchange systems have largely dealt with the case where the schemas are given a priori and transformations can only migrate data from the first schema to an instance of the second schema. In particular, the ability to perform data-metadata translations, transformation in which data is converted into metadata or metadata is converted into data, is largely ignored.