XML Structures for Relational Data

Wenyue Du, Mong Li Lee, Tok Wang LingWenyue Du, Mong Li Lee, Tok Wang Ling

Department of Computer Science

School of Computing

National University of Singapore

{duwenyue, leeml, lingtw}@comp.nus.edu.sg

XML Structures for Relational DataXML Structures for Relational Data

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ContentsContents

1. Introduction – Motivation– Related Works– Our Approach

2. Background– XML– XML DTD– Semantic Enrichment

3. Proposed Relational to XML Translation4. Comparison5. Conclusion

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1. Introduction1. Introduction

Outline

– Motivation– Related Works– Our Approach

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MotivationMotivation

XML is emerging as a standard for information publishing on the World Wide Web. However, the underlying data is often stored in traditional relational databases. Some mechanism is needed to translate the relational data into XML data.

IntroductionIntroduction

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Motivation Motivation (cont.)(cont.)

Generates XML structures that are able to describe the semantics and structures in underlying relational databases.

Obtains properly structured XML data without unnecessary redundancies and proliferation of disconnected XML elements.


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Related WorksRelated Works

• [1, 5, 6] basically focus on single relation translation. In order to handle a set of related relations, the relations are first denormalized to one single relation.

– The flat XML structure does not provide a good way to show the structure of data.

– It causes a lot of redundancies.


Relations:

Dept(D#, Dname)

Employee (E#, Ename, JoinDate, D#)

Maps to

<!ELEMENT Results(Employee*)><!ELEMENT Employee (EMPTY)> <!ATTLIST Employee E# CDATA #REQUIRED Ename CDATA #IMPLIED JoinDate CDATA #IMPLIED D# CDATA #REQUIRED DNAME CDATA #IMPLIED >

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Relations:

Dept (D#, Dname)

Employee (E#, Ename, JoinDate, D#)

Related Works Related Works (cont.)(cont.)

• [7] developed a method to generate a hierarchical DTD for XML data from a relational schema.

– It lacks of semantic enrichment. So it cannot handle more complex situations.


Is it an attribute of object or relationship?

<!ELEMENT Results(Employee*)>

<!ELEMENT Employee (Dept)>

<!ATTLIST Employee

E# ID #REQUIRED

Ename CDATA #IMPLIED

JoinDate CDATA #IMPLIED>

<!ELEMENT Dept (EMPTY)>

<!ATTLIST Dept … >

Maps to

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Our ApproachOur Approach

XML structures for relational data can be obtained by the following steps:

Sem anticEnrichm ent

O R A-SS toX M L-Schem a

AlgorithmT ranslation

R ulesR elationalSchem a

Sem antica llyEnriched

R elationalSchem a

O R A-SSSchem aD iagram

X M L-Schem a


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2. Background2. Background

Outline

– XML– XML Schema– Semantic Enrichment

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XMLXML

Basic constructs of XML:

– Element

– Attribute

– Reference (link) :

a relationship between resources (e.g. elements). It is specified by attaching specific attributes or sub-elements.

Background / XMLBackground / XML

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XML DTDXML DTD

Background / XML DTDBackground / XML DTD

XML document Corresponding DTD

<RESULTS>

<CUSTOMER CID=“C980054Z">

<CNAME>J. Tan</CNAME>

<AGE>36</AGE>

</CUSTOMER>

…

</RESULTS>

<!ELEMENT RESULTS (CUSTOMER*)>

<!ELEMENT CUSTOMER

(CNAME, AGE)>

<!ATTLIST CUSTOMER

CID ID #REQUIRED>

<!ELEMENT CNAME (#PCDATA)>

<!ELEMENT AGE (#PCDATA)>

A Document Type Definition (DTD) describes structure on an

XML document.

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Semantic EnrichmentSemantic Enrichment

• Semantic enrichment is a process that upgrades the semantics of databases, in order to explicitly express semantics that is implicit in the data.

Background / Semantic EnrichmentBackground / Semantic Enrichment

Such as various relationship types, cardinality constraints, etc.

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Extra information needed:Extra information needed:

• Functional Dependencies (FDs) and keys

• Inclusion dependencies (INDs)

e.g. STUDENT (S#, SNAME)

HOBBIES(S#, HOBBY)

HOBBIES[S#] STUDENT[S#]

• Semantic dependencies (SDs) (T.W. Ling & M.L. Lee, 1995)


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Semantic DependenciesSemantic Dependencies

Background / Semantic Enrichment Background / Semantic Enrichment

EMPLOYEE(E#, ENAME, JOINDATE, D#)

- JOINDATE is functionally dependent on only E#

- Assuming JOINDATE refers to the date on which an employee assumes duty with the department. We say that

JOINDATE is semantically dependent on {E#, D#}

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Semantic Enrichment using SD together with Semantic Enrichment using SD together with FD and INDFD and IND


To obtain:

Object relations and object attributes that represent regular and weak entity types, and their properties.

Relationship relations and relationship attributes that represent various relationship types such as binary, n-ary, recursive and ISA (inheritance), and their properties.

Mix-type relations: We need to split them into object relations and relationship relations

Fragments of object relations or relationship relations that represent multi-valued attributes of entity types or relationship types.

Cardinality constraints

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An Original Relational SchemaAn Original Relational Schema


COURSE (CODE, TITLE)

DEPT (D#, DNAME)

STUDENT (S#, SNAME)

TUTORIAL (T#, TUTORIALTITLE)

HOBBIES(S#, HOBBY)

STUDENTDEPT (S#, D#)

C_S (CODE, S#, GRADE)

ATTEND (CODE, T#, S#)

COURSEMEETING (CODE, S#,MEETINGHISTORY)

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The Semantically Enriched SchemaThe Semantically Enriched Schema


Object Relations:


DEPT (D#, DNAME)

STUDENT (S#, SNAME)


Fragment of Object Relations

HOBBIES(S#, HOBBY)

Relationship Relations:




Fragment of Relationship Relations


fragment of C_S

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3. Proposed Relational to XML Translation3. Proposed Relational to XML Translation

Outline

– ORA-SS Model– Relational Schema to ORA-SS Translation– ORA-SS to XML Schema Translation

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ORA-SS ModelORA-SS Model

ORA-SS (Object-Relationship-Attribute model for Semi-Structured data)

G. Dobbie, X.Y. Wu, T.W. Ling, M.L. Lee, “ORA-SS: An Object-Relationship-Attribute Model for Semi-structured Data”, TR 21/00, National Univ. of Singapore, 2001

Proposed Relational to XML Translation / ORA-SSProposed Relational to XML Translation / ORA-SS

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Concepts of ORA-SS Concepts of ORA-SS (cont.)(cont.)

Proposed Relational to XML Translation / ORA-SSProposed Relational to XML Translation / ORA-SS

C O U R SE

GRADE

ST U D EN T 1

C_S2,1:n,1:n

T U T O R IAL1

ATTEND3,1:n,1:n

ST U D EN T

S# SNAME

T U T O R IAL

T# TUTORIALTITLE

C_S

CODE TITLE

T_Ref

C_S_Ref

Object class

Ternary relationship

Binary relationship

Identifier ReferenceRelationship attribute

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Enriched Relational Schema to ORA-SS Schema Enriched Relational Schema to ORA-SS Schema TranslationTranslation

Objectives:

• Identify object classes and their attributes from object relations

• Identify relationship types and their attributes from relationship relations

• Identify hierarchical structure

• Generate ORA-SS schema

Enriched Relational Schema to ORA-SS Schema TranslationEnriched Relational Schema to ORA-SS Schema Translation

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Overview of Translation RulesOverview of Translation Rules

1. Object relation rules: to translate object relations

2. Relationship relation rules: to translate relationship relations

3. Combination rule: to be applied to the result obtained from the application of object and relationship relation rules, and generate the final ORA-SS schema.


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Rule O1: Mapping object relationsRule O1: Mapping object relations

Enriched Relational Schema to ORA-SS Schema Translation Enriched Relational Schema to ORA-SS Schema Translation /Object Relation Translation Rules/Object Relation Translation Rules

STUDENT(S#, SNAME)

ST U D EN T

SNAMES#

Single-valued attribute

Maps to

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Rule O2: Mapping fragment of object relationsRule O2: Mapping fragment of object relations

STUDENT(S#, SNAME)

HOBBIES(S#, HOBBY)

ST U D EN T

SNAMES# HOBBY*

Multivalued attribute

Maps to

Enriched Relational Schema to ORA-SS Schema Translation Enriched Relational Schema to ORA-SS Schema Translation /Object Relation Translation Rules/Object Relation Translation Rules

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Rule R1: Mapping 1-m/1-1 relationship relation Rule R1: Mapping 1-m/1-1 relationship relation

Objectives:

Reduce disconnected elements

Use parent-child structure Avoid unnecessary redundancies

Use references

Example:

ADVISOR(STAFF#, POSITION) // object relation

STUDENT(S#, SNAME) // object relation

STU_ADV(S#, STAFF#) //1-m relationship relation

Enriched Relational Schema to ORA-SS Schema Translation Enriched Relational Schema to ORA-SS Schema Translation /Relationship Relation Translation Rules/Relationship Relation Translation Rules

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Rule R1: Mapping 1-m/1-1 relationship relation Rule R1: Mapping 1-m/1-1 relationship relation (cont.)(cont.)

Case 1: All the objects (instances) of STUDENT participate in the relationship type STU_ADV

ADVISOR

STUDENT

STU_ADVMaps to

STU_ADV 2,0:n,1:1

Use parent-child structure


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Case 2:1. Not all the objects of STUDENT participate in STU_ADV.

2. STUDENT is already as a child object and all the objects of ADVISOR participate in STU_ADV .

Use parent-child structure

STUDENT

ADVISOR

STU_ADVMaps to

STU_ADV 2,0:1,1:n


or


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Case 3:There exist objects of STUDENT and ADVISOR do not participate in STU_ADV


STUDENT

ADVISOR1

STU_ADV orMaps to STU_ADV

2,*,?

Use reference

ADVISOR ADVISOR

STUDENT1

STU_ADV 2,*,?

STUDENT

A_Ref S_Ref


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Rule R2: Mapping m-n binary relationship relationRule R2: Mapping m-n binary relationship relation

C _S

G RADE

C O U R SE

TITLECODE

ST U D EN T

SNAMES#

GRADE

C O U R SE

TITLECODE

ST U D EN T

SNAMES#ST U D EN T 1

C_S,2,1:n,1:n

C_S C_S_REF

COURSE(CODE, TITLE)

C_S(S#, CODE, GRADE)

STUDENT (S#, SNAME)

GRADE

ST U D EN T

SNAMES#

C O U R SE

TITLECODEC O U R SE1

C_S,2,1:n,1:n

C_S C_S_REF

Preferred Mapping


Three ways to map:

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Other relationship relation rulesOther relationship relation rules

Fragment of relationship relation is translated similarly to the translation of the fragment of object relation.

N-ary relationship relation is translated using reference structures. The level of each referencing object may be determined by the aggregations.

If B ISA A, then B is mapped to a child object class (OB) of OA.


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Combination Rule: Combination Rule:

Example:

PERSON(SSNO, RACE) //object relation

STUDENT(S#, SSNO, MAJOR) //object relation

DEPT(D#, DNAME) //object relation

STU_DEPT(S#, D#) //relationship relation

Enriched Relational Schema to ORA-SS Schema Translation Enriched Relational Schema to ORA-SS Schema Translation /Combination Rule/Combination Rule

STUDENT ISA PERSON and one DEPT has many STUDENT.

In this case, STUDENT potentially has multiple parents (i.e., DEPT and PERSON).

to be applied to the result obtained from the application of object and relationship relation rules, and generate the final ORA-SS schema.

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Combination Rule: Combination Rule:

Current solution:

Use references (K. Williams, et al. January 2001)

-- It causes too many disconnected elements.

<!ELEMENT Results

(PERSON*, STUDENTS* DEPT*)>

<!ELEMENT PERSON (EMPTY)>

<!ATTLIST PERSON

SSNO ID #REQUIRED

RACE CDATA #IMPLIED

STU_REF1 IDREF #REQUIRED>

<!ELEMENT STUDENT (EMPTY)>

<!ATTLIST STUDENT

S# ID #REQUIRED

MAJOR CDATA #IMPLIED >

<!ELEMENT DEPT (EMPTY)>

<!ATTLIST DEPT

D# ID #REQUIRED

DNAME CDATA #IMPLIED

STU_REF2 IDREFS #REQUIRED>


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Combination Rule: Combination Rule: (cont.)(cont.)

The priorities of translations (in descending order)

1. ISA, etc. semantic relationship relations and their fragments // high semantic cohesion among these participating object classes

2. 1-1 and 1-m relationship relation and their fragments // potentially represented as hierarchy (p-c) structure

3. m-1 relationship relations and their fragments // potentially represented as hierarchy structure; preferably view as 1-m

4. m-n, n-ary relationship relations and their fragments

This rule is used to avoid or reduce potential multiple parents.


Our approach:

Translations are produced sequentially according to their priorities. The translation with the lowest priority will be carried out last.

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Combination Rule: Combination Rule: (cont.)(cont.)

S# ID #REQUIRED

MAJOR CDATA #IMPLIED >

<!ELEMENT DEPT (EMPTY)>

<!ATTLIST DEPT

D# ID #REQUIRED

DNAME CDATA #IMPLIED

D_S_REF IDREFS #REQUIRED>


S#

PER SO N

RACESSNO

D EPT

DNAMED#ST U D EN T

ISA,2,1:?,1:1

MAJOR

ST U D EN T1

D_S_REF

<!ELEMENT OurSolution (PERSON*, DEPT*)>

<!ELEMENT PERSON (STUDENT)>

<!ATTLIST PERSON

SSNO ID #REQUIRED

RACE CDATA #IMPLIED >

<!ELEMENT STUDENT (EMPTY)>

<!ATTLIST STUDENT

We map STUDENT to the child object class of PERSON first. Then map DEPT according to 1-m relationship relation rule. Thus, we may get the following result.

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A possible ORA-SS Schema diagram derived from A possible ORA-SS Schema diagram derived from universityuniversity database database

ST U D EN T

SNAMES#

D EPT

DNAMEST U D EN T 2 D#

STUDENTDEPT2,0:n,1:1

GRADE

C O U R SE

CODE ST U D EN T 1

C_S2,1:n,1:n

C_S

TITLE HOBBY*

T U T O R IAL1

ATTEND3,1:n,1:n

T U T O R IAL

T# TUTORIALTITLE

C_S

MEETINGHISTORY

*T_REF

D_S_REF

C_S_REF


Object Relations:


DEPT (D#, DNAME)

STUDENT (S#, SNAME)


Fragment of Object Relations

HOBBIES(S#, HOBBY)

Relationship Relations:




Fragment of Relationship Relations


fragment of C_S

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Input: an ORA-SS schema diagram SDOutput: an XML DTDBegin Start from the top of SD and proceed downward, for each object class O encountered do:Step 1. Sub-object classes of O <!ELEMENT O (subelementsList)>Step 2. For each attribute A of O Case (1) A is a single valued simple attribute <!ATTLIST O A type> Case (2) A is a single valued composite attribute, replace A with its components and add to <!ATTLIST O attributename type> Case (3) A is a multivalued simple attribute <!ELEMENT A(#PCDATA)> Case (4) A is a multivalued composite attribute <!ELEMENT A(EMPTY)> A’s components <!ATTLIST A componentName type>Step 3. For each relationship attribute A under O, add A to subelementsList in <!ELEMENT O(subelementsList)>. Case (1) A is a simple attribute <!ELEMENT A(#PCDATA)>. Case (2) A is a composite attribute <!ELEMENT A(EMPTY)>, A’s components <!ATTLIST A componentName type>

Algorithm: Mapping ORA-SS Schema DiagramAlgorithm: Mapping ORA-SS Schema Diagram to XML DTD to XML DTD

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Algorithm: Mapping ORA-SS Schema Diagram to XML DTDAlgorithm: Mapping ORA-SS Schema Diagram to XML DTD

<!ELEMENT UNIVERSITY (COURSE*, STUDENT*, DEPT*, TUTORIAL*)><!ELEMENT COURSE (STUDENT1*)> <!ATTLIST COURSE CODE ID #REQUIRED TITLE CDATA #IMPLIED> <!ELEMENT STUDENT1 (MEETINGHIS*,TUTORIAL1*)> <!ATTLIST STUDENT1 C_S_REF IDREF #REQUIRED GRADE CDATA #IMPLIED> <!ELEMENT MEETINGHIS (#PCDATA)> <!ELEMENT TUTORIAL1 (EMPTY)> <!ATTLIST TUTORIAL1 T_REF IDREF #REQUIRED><!ELEMENT STUDENT (HOBBIES*)>

<!ATTLIST STUDENT S# ID #REQUIRED SNAME CDATA #IMPLIED> <!ELEMENT HOBBIES (#PCDATA)><!ELEMENT DEPT (STUDENT2*)> <!ATTLIST DEPT D# ID #REQUIRED DNAME CDATA #IMPLIED> <!ELEMENT STUDENT2 (EMPTY)> <!ATTLIST STUDENT2 D_S_REF IDREF #IMPLIED><!ELEMENT TUTORIAL(EMPTY)> <!ATTLIST TUTORIAL T# ID #REQUIRED TUTORIAL_TITLE CDATA #IMPLIED>

The obtained XML structures (DTD)The obtained XML structures (DTD)

4. Comparison4. Comparison

Rich structured and represents the real world accurately

Yes ( ) [7], This paper

Partially [3]

No [1, 5, 6]

The representation of various relationship types and their attributes

Yes ( ) This paper

Partially [7]

No [1, 3, 5, 6]

Number of disconnected elements Few ( ) [7], This paper

Many Naïve approaches

Unnecessary redundancies Avoidable ( ) This paper

Partially [3, 7]

Many [1, 5, 6]

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5 Conclusion5 Conclusion

Method proposed in this paper achieves

Generation of semantically sound XML structures for relational data possible

Generation of properly structured XML data without unnecessary redundancies and proliferation of disconnected XML elements possible

ReferencesReferences

[1] S. Banerjee, et al “Oracle 8i – The XML Enabled Data Management System”,

Proc. 16th Int’l Conf. on Data Engineering, 2000

[2] G. Dobbie, X.Y. Wu, T.W. Ling, M.L. Lee, “ORA-SS: An Object-

Relationship- ttribute Model for Semi-structured Data”, TR 21/00, NUS, 2001

[3] D.W. Lee, M. Mani, F. Chiu, W.W Chu, “Nesting-based Relational-to-XML

Schema Translation”, Proc, 4th Int’l Workshop on Web and Databases, 2001

[4] T.W. Ling, M.L. Lee, “Relational to Entity-Relationship Schema Translation

Using Semantic and Inclusion Dependencies”, In Journal of Integrated

Computer-Aided Engineering, pages 125-145, 1995

[5] SYBASE, “Using XML with the Sybase Adaptive Server SQL Databases, A

Technical Whitepaper”, http://www.sybase.com,2000

[6] V. Turau, “Making Legacy Data Accessible for XML Applications”,

http://www.informatik.fh-wiesbaden.de/~turau/veroeff.html1999

[7] K. Williams, et al., “XML Structures for Existing Databases”, http://www-

106.ibm.com/developerworks/library/x-struct/ January 2001

[8] W.Y. Du, M.L. Lee, T.W. Ling, “XML Structures for Relational Data”,

Proc. 2nd Int’l Conf. on Web Information Systems Engineering (WISE) , IEEE Computer Society, 2001

Documents

XML Structures for Relational Data