VALIDATION OF MAPPINGS BETWEEN DATA MODELS

1. VALIDATION OF MAPPINGS BETWEEN DATA MODELS Guillem Rull Technical University of Catalonia (UPC) Barcelona, Spain Current State of the Research • 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. • The Motivation • Mappings 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. • 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. • We have proved that the four properties can be expressed in terms of query liveliness in a relational database. • 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. • 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 are currently working on computing explanations when the properties do not hold. Example of Mapping • Identify relevant properties to validate. • Validate mappings according to these properties in the context of relational databases. • Extend the previous results to mappings between different types of models (XML, OO, etc.) • Develop a tool able to, given a mapping and its models, perform tests to check the desirable properties. • Source model: employees(name, category, happiness-degree) categories(name, salary) • Target model: happy-employees(name, happiness-degree) all-employees(name, salary) • Mapping formulas: select name, happiness-degree from employees where happiness-degree > 10 select name, happiness-degree from happy-employees  select employees.name, salary from employees, categories whereemployees.category = categories.name select name, salary from all-employees  Microsoft is a registered trademark of Microsoft Corporation