Latest revision as of 15:48, 23 November 2015

LAV Mediation

There are two main approached for Mediating in Data Integration

• GAV Mediation - defining global relations in terms of local
• LAV Mediation - defining local relations in terms of global

LAV - Local-as-View Mediation

• local relations are defined as views (queries) over global relations
• goal: define the global schema in such a way that individual definitions don't change when new data sources are added or old are removed
• See some notation in Mediator (Data Integration)

LAV Mapping

LAV Mapping

• mapping $S \subseteq Q$ for some Conjunctive Query $Q(\vec{x}) \leftarrow A_1(\vec{u}_1), \ ..., \ A_k(\vec{u}_k)$ over the global relations
• this gives loose-coupling between global and local schemas

FOL Semantics:

• $\forall x_1, ..., x_n \Big[ S(x_1, ..., x_n) \Rightarrow \exists \ y_1, ..., y_m \ : \ A_1(\vec{u}_1) \ \land \ ... \ \land \ A_k(\vec{u}_k) \Big]$
• $S(x_1, ..., x_n)$ - head of a view
• $y_1, ..., y_m$ - existential variables
• $A_1(\vec{u}_1) \ \land \ ... \ \land \ A_k(\vec{u}_k)$ - body

Example

Suppose we have this global schema

• Student(studentName),
• EuropeanStudent(studentName),
• University(uniName),
• NonEuropeanStudent(studentName),
• FrenchUniversity(uniName),
• EuropeanUniversity(uniName),
• NonEuropeanUniversity(uniName),
• Program(title),
• MasterProgram(title),
• EnrolledInProgram(studentName, title),
• Course(code),
• EnrolledInCourse(studentName, code),
• PartOf(code, title),
• RegisteredTo(studentName, uniName),
• OfferedBy(title, uniName).

Data sources from the previous examples

• S1.Catalogue(nomUniv, programme). - programs in French universities
• S2.Erasmus(student, course, univ). - European Erasmus students
• S3.CampusFr(student, program, university). - foreign students in France
• S4.Mundus(program, course). - international master programs

LAV Mappings:

• $m_1$: S1.Catalogue(U, P) $\subseteq$ FrenchUniversity(U), Program(P), OfferedBy(P, U), OfferedBy(P', U), MasterProgram(P')
• $m_2$: S2.Erasmus(S, C, U) $\subseteq$ Student(S), EnrolledInCourse(S, C), PartOf(C, P), OfferedBy(P, U), EuropeanUniversity(U), EuropeanUniversity(U') RegisteredTo(S, U'), U $\neq$ U'
• $m_3$: S3.CampusFr(S, P, U) $\subseteq$ NonEuropeanStudent(S), Program(P), EnrolledInProgram(S, P), OfferedBy(P, U), FrenchUniversity(U), RegisteredTo(S, U)
• $m_4$: S4.Mundus(P, C) $\subseteq$ MasterProgram(P), OfferedBy(P, U), OfferedBy(P, U'), EuropeanUniversity(U), NonEuropeanUniversity(U'), PartOf(C, P)

So,

• LAV mapping can be seen as a description of the data source in terms of the global schema
• for example, Erasmus students ($m_2$) are
  • European students
  • enrolled in an European university
  • that European university is different from their home university
  • they remain registered in their home university

Loose-Coupling

• This gives loose-coupling between local and global relations
• which is important when participating data sources change frequently

Query Answering

suppose we're interested in Master students

• define the following query
• $\text{MasterStudent}(E) \leftarrow \text{Student}(E), \text{EnrolledInProgram}(E, M), \text{MasterProgram}(M).$
• how to find which data sources to query?
• rewriting process is more complex, than for GAV

Algorithms to do that

• Bucket Algorithm
• Minicon Algorithm
• Inverse-Rules Algorithm

Sources

• Web Data Management (book)