VALIDATION OF MAPPINGS BETWEEN

DATA MODELSGuillem Rull

Technical University of Catalonia (UPC)

Barcelona, Spain

The MotivationMappings are key elements for any application requiring interaction of heterogeneous data.

A lot of research efforts have been done to automate the mapping creation process.

However, all approaches require human feedback at some point, to solve semantic heterogeneities.

It is thus necessary be able to check whether the resulting mappings satisfy the expected needs and requirements. Few work has been done in this area.

The Research

The main goal is to propose a method for testing whether a mapping satisfies some desirable properties.

We will extend the CQC method which we successfully applied to the validation of database schemas.

Main steps:

We have proved that the four properties can be expressed in terms of query liveliness in a relational database.

1.Identify relevant properties to validate.

2.Validate mappings according to these properties in the context of relational databases.

3.Extend the previous results to mappings between different types of models (XML, OO, etc.)

4.Develop a tool able to, given a mapping and its models, perform tests to check the desirable properties.

•Mapping inference allows us to check for redundant mapping formulas.

•Mapping losslessness allows us to check whether some data is captured by mapping. It is a generalization of query answerability.

•Query answerability checks whether the exact answer of a query is preserved by mapping.

•Mapping satisfiability allows us to ensure that the mapping contains no contradiction.

•A query is not lively if it returns an empty answer for all database instances. We can check it with the CQC method.

•We can define a new schema putting together the mapped models and incorporating the mapping in form of additional constraints.

•Then, for each property we can define a query such that its liveliness determines if the property holds or not.

Two important properties of mappings are defined in the literature: mapping inference and query answerability.

We have also proposed and formalized two additional properties: mapping satisfiability and mapping losslessness.

Current State of the Research

We are currently working on computing explanations when the properties do not hold.

Example of Mapping

employees(name, category, happiness-degree)categories(name, salary)

happy-employees(name, happiness-degree) all-employees(name, salary)

select name, happiness-degreefrom employeeswhere happiness-degree > 10select employees.name, salaryfrom employees, categorieswhere employees.category = categories.name

select name,happiness-degreefrom happy-employees

select name, salaryfrom all-employees

Mapping formulas:

Source model:

Target model:

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