Wenyue Du, Mong Li Lee, Tok Wang Ling Department of Computer Science School of Computing National University of Singapore {duwenyue, leeml, XML Structures for Relational Data

2 Contents 1. Introduction –Motivation –Related Works –Our Approach 2. Background –XML –XML DTD –Semantic Enrichment 3. Proposed Relational to XML Translation 4. Comparison 5. Conclusion

3 1. Introduction Outline –Motivation –Related Works –Our Approach

4 Motivation 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. Introduction

5 Motivation (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.Introduction

6 Related 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.Introduction Relations: Dept(D#, Dname) Employee (E#, Ename, JoinDate, D#) Maps to <!ATTLIST Employee E# CDATA #REQUIRED Ename CDATA #IMPLIED JoinDate CDATA #IMPLIED D# CDATA #REQUIRED DNAME CDATA #IMPLIED >

7 Relations: Dept (D#, Dname) Employee (E#, Ename, JoinDate, D#) Related Works (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. Introduction Is it an attribute of object or relationship? <!ATTLIST Employee E# ID #REQUIRED Ename CDATA #IMPLIED JoinDate CDATA #IMPLIED> Maps to

8 Our Approach XML structures for relational data can be obtained by the following steps:Introduction

9 2. Background Outline –XML –XML Schema –Semantic Enrichment

10 XML 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 / XML

11 XML DTD Background / XML DTD XML documentCorresponding DTD J. Tan 36 … <!ELEMENT CUSTOMER (CNAME, AGE)> <!ATTLIST CUSTOMER CID ID #REQUIRED> A Document Type Definition (DTD) describes structure on an XML document.

12 Semantic 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 Enrichment Such as various relationship types, cardinality constraints, etc.

13 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) Background / Semantic Enrichment

14 Semantic Dependencies 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#}

15 Semantic Enrichment using SD together with FD and IND Background / Semantic Enrichment 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

16 An Original Relational Schema Background / Semantic Enrichment 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)

17 The Semantically Enriched Schema Background / Semantic Enrichment Object Relations: COURSE (CODE, TITLE) DEPT (D#, DNAME) STUDENT (S#, SNAME) TUTORIAL (T#, TUTORIALTITLE) Fragment of Object Relations HOBBIES(S#, HOBBY) Relationship Relations: STUDENTDEPT (S#, D#) C_S (CODE, S#, GRADE ) ATTEND (CODE, T#, S#) Fragment of Relationship Relations COURSEMEETING (CODE, S#, MEETINGHISTORY ) fragment of C_S

18 3. Proposed Relational to XML Translation Outline –ORA-SS Model –Relational Schema to ORA-SS Translation –ORA-SS to XML Schema Translation

19 ORA-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-SS

20 Concepts of ORA-SS (cont.) Proposed Relational to XML Translation / ORA-SS Object class Ternary relationship Binary relationship Identifier Reference Relationship attribute

21 Enriched Relational Schema to ORA-SS Schema Translation 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 Translation

22 Overview 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. Enriched Relational Schema to ORA-SS Schema Translation

23 Rule O1: Mapping object relations Enriched Relational Schema to ORA-SS Schema Translation /Object Relation Translation Rules STUDENT(S#, SNAME) Single-valued attribute Maps to

24 Rule O2: Mapping fragment of object relations STUDENT(S#, SNAME) HOBBIES(S#, HOBBY) Multivalued attribute Maps to Enriched Relational Schema to ORA-SS Schema Translation /Object Relation Translation Rules

25 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 /Relationship Relation Translation Rules

26 Rule R1: Mapping 1-m/1-1 relationship relation (cont.) Case 1: All the objects (instances) of STUDENT participate in the relationship type STU_ADV ADVISOR STUDENT STU_ADV Maps to STU_ADV 2,0:n,1:1 Use parent-child structure Enriched Relational Schema to ORA-SS Schema Translation /Relationship Relation Translation Rules

27 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_ADV Maps to STU_ADV 2,0:1,1:n Rule R1: Mapping 1-m/1-1 relationship relation (cont.) or Enriched Relational Schema to ORA-SS Schema Translation /Relationship Relation Translation Rules

28 Case 3: There exist objects of STUDENT and ADVISOR do not participate in STU_ADV Rule R1: Mapping 1-m/1-1 relationship relation (cont.) STUDENT ADVISOR1 STU_ADV or Maps to STU_ADV 2,*,? Use reference ADVISOR STUDENT1 STU_ADV 2,*,? STUDENT A_RefS_Ref Enriched Relational Schema to ORA-SS Schema Translation /Relationship Relation Translation Rules

29 Rule R2: Mapping m-n binary relationship relation COURSE(CODE, TITLE) C_S(S#, CODE, GRADE) STUDENT (S#, SNAME) Preferred Mapping Enriched Relational Schema to ORA-SS Schema Translation /Relationship Relation Translation Rules Three ways to map:

30 Other 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 (O B ) of O A. Enriched Relational Schema to ORA-SS Schema Translation /Relationship Relation Translation Rules

31 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 /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.

32 Combination Rule: Current solution: Use references (K. Williams, et al. January 2001) -- It causes too many disconnected elements. <!ELEMENT Results (PERSON*, STUDENTS* DEPT*)> <!ATTLIST PERSON SSNO ID #REQUIRED RACE CDATA #IMPLIED STU_REF1 IDREF #REQUIRED> <!ATTLIST STUDENT S# ID #REQUIRED MAJOR CDATA #IMPLIED > <!ATTLIST DEPT D# ID #REQUIRED DNAME CDATA #IMPLIED STU_REF2 IDREFS #REQUIRED> Enriched Relational Schema to ORA-SS Schema Translation /Combination Rule

33 Combination Rule: (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 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. Enriched Relational Schema to ORA-SS Schema Translation /Combination Rule Our approach: Translations are produced sequentially according to their priorities. The translation with the lowest priority will be carried out last.

34 Combination Rule: (cont.) S# ID #REQUIRED MAJOR CDATA #IMPLIED > <!ATTLIST DEPT D# ID #REQUIRED DNAME CDATA #IMPLIED D_S_REF IDREFS #REQUIRED> Enriched Relational Schema to ORA-SS Schema Translation /Combination Rule <!ATTLIST PERSON SSNO ID #REQUIRED RACE CDATA #IMPLIED > <!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.

35 A possible ORA-SS Schema diagram derived from university database Enriched Relational Schema to ORA-SS Schema Translation Object Relations: COURSE (CODE, TITLE) DEPT (D#, DNAME) STUDENT (S#, SNAME) TUTORIAL (T#, TUTORIALTITLE) Fragment of Object Relations HOBBIES(S#, HOBBY) Relationship Relations: STUDENTDEPT (S#, D#) C_S (CODE, S#, GRADE) ATTEND (CODE, T#, S#) Fragment of Relationship Relations COURSEMEETING (CODE, S#,MEETINGHISTORY) fragment of C_S

36 Input: an ORA-SS schema diagram SD Output: an XML DTD Begin Start from the top of SD and proceed downward, for each object class O encountered do: Step 1. Sub-object classes of O Step 2. For each attribute A of O Case (1) A is a single valued simple attribute Case (2) A is a single valued composite attribute, replace A with its components and add to Case (3) A is a multivalued simple attribute Case (4) A is a multivalued composite attribute A’s components Step 3. For each relationship attribute A under O, add A to subelementsList in. Case (1) A is a simple attribute. Case (2) A is a composite attribute, A’s components Algorithm: Mapping ORA-SS Schema Diagram to XML DTD

37 Algorithm: Mapping ORA-SS Schema Diagram to XML DTD <!ATTLIST TUTORIAL T# ID #REQUIRED TUTORIAL_TITLE CDATA #IMPLIED> The obtained XML structures (DTD)

4. 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 elementsFew ( )[7], This paper ManyNaïve approaches Unnecessary redundanciesAvoidable ( )This paper Partially[3, 7] Many[1, 5, 6]

39 5 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

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