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GLASS : A Graphical Query Language for Semi-Structured Data

GLASS : A Graphical Query Language for Semi-Structured Data. Wei Ni Tok Wang Ling Department of Computer Science National University of Singapore, Singapore E-mail: {niwei, lingtw}@comp.nus.edu.sg. Roadmap. Introduction and motivation ORA-SS  the data model of our language

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GLASS : A Graphical Query Language for Semi-Structured Data

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  1. GLASS: A Graphical Query Language for Semi-Structured Data Wei Ni Tok Wang Ling Department of Computer Science National University of Singapore, Singapore E-mail: {niwei, lingtw}@comp.nus.edu.sg DASFAA2003, Kyoto, Japan

  2. Roadmap • Introduction and motivation • ORA-SS  the data model of our language • GLASS, our graphical query language • Related works and comparison • Conclusion and future work DASFAA2003, Kyoto, Japan

  3. 1. Introduction and motivation • XML: a standard for representation, manipulation and exchange of data. • Query engines: a crucial application to exploit the full power of XML. • XQuery: a standard for querying XML data which is too difficult for non-technical users to use. • Graphical query language: a way to help users query XML data. DASFAA2003, Kyoto, Japan

  4. 1. Introduction and motivation (Cont.) • Criteria of a good query language • Expressiveness • Completeness • User-friendliness • Graphical Query Language: user-friendly and easy understanding DASFAA2003, Kyoto, Japan

  5. There is a binary relationship type, named as “cs”, between course and student where one course may has one or many students and one students can take one or many courses. Example 1: <grade> belongs to the binary relationship type “cs” between <course> and <student> <!ELEMENT department (course+)> <!ATTLIST department name ID #REQUIRED> <!ELEMENT course (title?, student+)> <!ATTLIST course code ID #REQUIRED> <!ELEMENT title PCDATA> <!ELEMENT student (name?, grade+)> <!ATTLIST student number #IMPLIED> <!ELEMENT name PCDATA> <!ELEMENT grade PCDATA> The DTD of “Department.xml” The ORA-SS schema diagram of “Department.xml” department 2, 1:n, 1:1 course name cs, 2, 1:n, 1:n student code title cs number name grade 2. ORA-SS the data model of our language • ORA-SS (Object-Relationship-Attribute model for Semi-Structured data) :a rich semantic data model. DASFAA2003, Kyoto, Japan

  6. 3. GLASSour graphical query language • GLASS (Graphical Query Language for Semi-Structured Data) • Targets of GLASS • support various queries including Aggregation Functions and Negation; • be clear and concise without ambiguity; • provide “freedom” to non-technical users in querying. DASFAA2003, Kyoto, Japan

  7. 3. GLASSour graphical query language3.1 General concepts in GLASS • Data icons • Rectangle: the object class in ORA-SS, non-terminal element in XML (element with subelements or attributes). • Circle: the attribute in ORA-SS, terminal element with PCDATA only and the attribute (or attribute list) in XML. • Connections • Arrow: relationship type • Dashed arrow: IDREF in XML • Line: link between output and original entities DASFAA2003, Kyoto, Japan

  8. 3. GLASSour graphical query language3.1 General concepts in GLASS (Cont.) • Box: the group entity in GLASS query graphs that consists of all rectangles or circles inside the box. • Derived entities: derived object classes and attributes are represented as dashed rectangles and dashed circles whichare new data types defined by users. • Condition Logic Window(CLW):an optional part in a GLASS query to write logic expressions and statements (e.g. IF-THEN) for complex query conditions and/or constructions. DASFAA2003, Kyoto, Japan

  9. 3. GLASSour graphical query language3.1 General concepts in GLASS (Cont.) • Path Identifier • a unique name given to data icons or boxes; • indicated by prefix “$”. • Condition Identifier • a unique name given to the connections; • without prefix “$”. • Logic Expression:specifies the logic in query conditions • Statement:helps construct complex outputs DASFAA2003, Kyoto, Japan

  10. Query condition Result construction CLW Logic expressions and statements 3. GLASSour graphical query language3.1 General concepts in GLASS (Cont.) Structure of GLASS query graph The black parts are optional. DASFAA2003, Kyoto, Japan

  11. Example 1: <?xml version = “1.0” standalone = “no” encoding = “UTF-8”> <DOCTYPE BOOK SYSTEM “Department.dtd”> <department name=“CS”> <course code=“201”> <title>Software Engineering</title> <student number=“1001”> <name>John Smith</name> <grade>A</grade> </student> <student number=“1002”> <name>Mel Green</name> <grade>C</grade> </student> </course> <course code=“303”> <title>Database Design</title> <student number=“1001”> <name>John Smith</name> <grade>B</grade> </student> </course> </department> <!ELEMENT department (course+)> <!ATTLIST department name ID #REQUIRED> <!ELEMENT course (title?, student+)> <!ATTLIST course code ID #REQUIRED> <!ELEMENT title PCDATA> <!ELEMENT student (name?, grade+)> <!ATTLIST student number #IMPLIED> <!ELEMENT name PCDATA> <!ELEMENT grade PCDATA> The DTD of “Department.xml” The ORA-SS schema diagram of “Department.xml” The content of “Department.xml” department 2, 1:n, 1:1 course name cs, 2, 1:n, 1:n student code title cs number name grade 3. GLASSour graphical query language3.2 Output construction DASFAA2003, Kyoto, Japan

  12. The default entity type implies both attributes and simple subelements of course element The default number of level is “1”. We use “/2” to represent 2 levels under element course. department 2, 1:n, 1:1 course name cs, 2, 1:n, 1:n student code title cs number name grade 3. GLASSour graphical query language3.2 Output construction (Cont.) (a) Extract courses and all information one level under course elements by using the default output method SOURCE DATA <?xml version = “1.0” standalone = “no” encoding = “UTF-8”> <DOCTYPE BOOK SYSTEM “Department.dtd”> <department name=“CS”> <course code=“201”> <title>Software Engineering</title> <student number=“1001”> <name>John Smith</name> <grade>A</grade> </student> <student number=“1002”> <name>Mel Green</name> <grade>C</grade> </student> </course> <course code=“303”> <title>Database Design</title> <student number=“1001”> <name>John Smith</name> <grade>B</grade> </student> </course> </department> <?xml version = “1.0” standalone = “no” encoding = “UTF-8”> <DOCTYPE BOOK SYSTEM “Department.dtd”> <department name=“CS”> <course code=“201”> <title>Software Engineering</title> <student number=“1001”> <name>John Smith</name> <grade>A</grade> </student> <student number=“1002”> <name>Mel Green</name> <grade>C</grade> </student> </course> <course code=“303”> <title>Database Design</title> <student number=“1001”> <name>John Smith</name> <grade>B</grade> </student> </course> </department> QUERY QUERY RESULT course <course code=“201”> <title>Software Engineering</title> </course> <course code=“303”> <title>Database Design</title> </course> In the default output method, everything will be kept in the original style from source data. DASFAA2003, Kyoto, Japan

  13. “*” is a wildcard which means all nested level under course element. department 2, 1:n, 1:1 course name cs, 2, 1:n, 1:n student code title cs number name grade 3. GLASSour graphical query language3.2 Output construction (Cont.) (b) Extract courses and all information at all levels under course elements by using the default output method SOURCE DATA <?xml version = “1.0” standalone = “no” encoding = “UTF-8”> <DOCTYPE BOOK SYSTEM “Department.dtd”> <department name=“CS”> <course code=“201”> <title>Software Engineering</title> <student number=“1001”> <name>John Smith</name> <grade>A</grade> </student> <student number=“1002”> <name>Mel Green</name> <grade>C</grade> </student> </course> <course code=“303”> <title>Database Design</title> <student number=“1001”> <name>John Smith</name> <grade>B</grade> </student> </course> </department> QUERY QUERY RESULT course <course code=“201”> <title>Software Engineering</title> <student number=“1001”> <name>John Smith</name> <grade>A</grade> </student> <student number=“1002”> <name>Mel Green</name> <grade>C</grade> </student> </course> <course code=“303”> <title>Database Design</title> <student number=“1001”> <name>John Smith</name> <grade>B</grade> </student> </course> * DASFAA2003, Kyoto, Japan

  14. The circle with “@” inside implies all attributes of course element in the original XML document department 2, 1:n, 1:1 course name cs, 2, 1:n, 1:n student code title cs number name grade 3. GLASSour graphical query language3.2 Output construction (Cont.) (c) Extract courses with all attributes of course element in the original XML document SOURCE DATA <?xml version = “1.0” standalone = “no” encoding = “UTF-8”> <DOCTYPE BOOK SYSTEM “Department.dtd”> <department name=“CS”> <course code=“201”> <title>Software Engineering</title> <student number=“1001”> <name>John Smith</name> <grade>A</grade> </student> <student number=“1002”> <name>Mel Green</name> <grade>C</grade> </student> </course> <course code=“303”> <title>Database Design</title> <student number=“1001”> <name>John Smith</name> <grade>B</grade> </student> </course> </department> QUERY QUERY RESULT course <course code=“201”></course> <course code=“303”></course> @ DASFAA2003, Kyoto, Japan

  15. The circle with “e” inside indicates all simple subelements of course element. department 2, 1:n, 1:1 course name cs, 2, 1:n, 1:n student code title cs number name grade 3. GLASSour graphical query language3.2 Output construction (Cont.) (d) Extract courses and all subelements at one level under course elements (except the attributes of course elements) SOURCE DATA <?xml version = “1.0” standalone = “no” encoding = “UTF-8”> <DOCTYPE BOOK SYSTEM “Department.dtd”> <department name=“CS”> <course code=“201”> <title>Software Engineering</title> <student number=“1001”> <name>John Smith</name> <grade>A</grade> </student> <student number=“1002”> <name>Mel Green</name> <grade>C</grade> </student> </course> <course code=“303”> <title>Database Design</title> <student number=“1001”> <name>John Smith</name> <grade>B</grade> </student> </course> </department> QUERY QUERY RESULT course <course> <title>Software Engineering</title> </course> <course> <title>Database Design</title> </course> e DASFAA2003, Kyoto, Japan

  16. The blank circle implies both attributes and simple subelements of course element Since only the entities at one level under course element are displayed, the student number at the second level under course doesn’t appear in the result. The blank rectangle stands for all complex subelements of course element. department 2, 1:n, 1:1 course name cs, 2, 1:n, 1:n student code title cs number name grade 3. GLASSour graphical query language3.2 Output construction (Cont.) (e) Extract courses with their attributes and/or simple subelements as well as the contents of complex subelements at one level under course element. SOURCE DATA <?xml version = “1.0” standalone = “no” encoding = “UTF-8”> <DOCTYPE BOOK SYSTEM “Department.dtd”> <department name=“CS”> <course code=“201”> <title>Software Engineering</title> <student number=“1001”> <name>John Smith</name> <grade>A</grade> </student> <student number=“1002”> <name>Mel Green</name> <grade>C</grade> </student> </course> <course code=“303”> <title>Database Design</title> <student number=“1001”> <name>John Smith</name> <grade>B</grade> </student> </course> </department> QUERY QUERY RESULT <course code=“201”> <title>Software Engineering</title> <student></student> <student></student> </course> <course code=“303”> <title>Database Design</title> <student></student> </course> course DASFAA2003, Kyoto, Japan

  17. course course @ title title e code The links here imply that the values of the new defined title attribute and code element come from the title and code in the original data. 3. GLASSour graphical query language3.2 Output construction (Cont.) (f) Extract courses with their titles as attributes and codes as subelements in the output. SOURCE DATA <?xml version = “1.0” standalone = “no” encoding = “UTF-8”> <DOCTYPE BOOK SYSTEM “Department.dtd”> <department name=“CS”> <course code=“201”> <title>Software Engineering</title> <student number=“1001”> <name>John Smith</name> <grade>A</grade> </student> <student number=“1002”> <name>Mel Green</name> <grade>C</grade> </student> </course> <course code=“303”> <title>Database Design</title> <student number=“1001”> <name>John Smith</name> <grade>B</grade> </student> </course> </department> QUERY QUERY RESULT <course title=“Software Engineering”> <code>201</code> </course> <course title=“Database Design”> <code>303</code> </course> code a demonstration of the conversion between attribute and subelement DASFAA2003, Kyoto, Japan

  18. course course * code = ‘2%’ The output course in RHS is the course that satisfies the condition in LHS 3. GLASSour graphical query language3.3 Basic query operatorsSelection To select all courses whose codes begin with “2”, we can write an XQuery language as: FOR $c IN $department/course WHERE $c/@code/data() = ‘2%’ RETURN $c DASFAA2003, Kyoto, Japan

  19. course title Without the specification of subelements or attributes, the title will remain unchanged as a subelement of course in the result. 3. GLASSour graphical query language3.4Basic query operatorsProjection To project all courses with their titles, XQuery will give the following expression: FOR $c IN $department/course RETURN <course>{ $c/title }</course> DASFAA2003, Kyoto, Japan

  20. course code description title 3. GLASSour graphical query language3.5 Basic query operators Join Suppose we have another XML data named as “Description.xml” containing the descriptions of all courses. <!ELEMENT course (title?, description)> <!ATTLIST course code ID #REQUIRED> <!ELEMENT title PCDATA> <!ELEMENT description PCDATA> The ORA-SS schema diagram of “Description.xml” The DTD of “Description.xml” DASFAA2003, Kyoto, Japan

  21. FROM Description.xml FROM Department.xml course course course * The URLs of data sources description description code 3. GLASSour graphical query language3.5 Basic query operators  Join (Cont.) Query: To extract everything of the courses from “Department.xml”, which have descriptions in “Description.xml”, and put the corresponding descriptions under the courses in the results. DASFAA2003, Kyoto, Japan

  22. avg_grade is a derived entity and it will be constructed as a subelement of “course” course course _group student e To group student under course avg_grade cs AVG grade Aggregation functions are available after “_group” functionality is done. 3. GLASSour graphical query language3.6 Aggregation functionsgroup & average Query: For all courses, display courses with their information (in default way) and the average grade of each course. The character “e” inside the dotted circle implies the avg_grade is a element type DASFAA2003, Kyoto, Japan

  23. 3. GLASSour graphical query language3.6 Aggregation functionsgroup & average Query: For all courses, display courses with their information (in default way) and the average grade of each course. (Presented by XQuery expressions as follows) for $ccd indistinct-values(document("Department.xml")//course/@code) let $c := document("Department.xml")//course, $s := $c/student where $c/@code = $ccd return <course code = "{$c/@code}" > { $c/title, } <avg_grade> {avg($s/grade)} </avg_grade> </course> DASFAA2003, Kyoto, Japan

  24. Example 2: The <author> order is important to the <book> book 2, +, +, < author content title isbn firstname lastname 3. GLASSour graphical query language3.7 Query order sensitive data Suppose we have an order sensitive data “Bib.xml”. The ORA-SS schema diagram of “Bib.xml”, order-sensitive data DASFAA2003, Kyoto, Japan

  25. book “[1]” means the first element in order [1] author isbn title 3. GLASSour graphical query language3.7 Query order sensitive data (Cont.) Query: Display all books with their isbn’s, titles and their first authors . DASFAA2003, Kyoto, Japan

  26. Ternary relation among <project>, <member> and <publication> where one member in one project can have 0 or many publications; and one publication can belong to one or many (project, member) pairs. Example 3: project 2, +, + member id name 3, *, + publication name job_title number title 3. GLASSour graphical query language3.8 Advanced features of GLASS Suppose we have a more complex XML data about projects, members and publications. The ORA-SS schema diagram of the data about “project, member and publication” DASFAA2003, Kyoto, Japan

  27. member member The box _group project name CNT < 5 name = ‘S%’ To group projects under member _group To group publications under each pair of (member, project) publication “CNT” means “count”. (“CNT” do count without eliminating duplicates.) We can also use other aggregation functions like SUM, AVG, etc. CNT > 6 3. GLASSour graphical query language3.8.1 Group entity  the use of box Query: Display the members with names who have taken part in less than 5 projects but written more than 6 publications in some project they attended, and their names begin with the character “S”. DASFAA2003, Kyoto, Japan

  28. member member _group _group project project CNT < 5 name = ‘S%’ name = ‘S%’ CNT < 5 _group Select publication only GROUP BY <member> CNT_UNIQUE will eliminate duplicates in counting. _group publication Select publication GROUP BY <member, project> pairs CNT_UNIQUE > 6 publication CNT > 6 member member name name 3. GLASSour graphical query language3.8.1 Group entity  the use of box (Cont.) The previous query: Display the members with names who have taken part in less than 5 projects but written more than 6 publications in some project they attended, and their names begin with the character “S”. A new query: Display the members with names who have totally taken part in less than 5 projects and totally written more than 6 publications, and their names begin with character“S”. DASFAA2003, Kyoto, Japan

  29. The colons are not part of the identifiers but distinguish the identifiers from relationship type names. member member : A : publication name The identifier “A” means has a publication with title = “Introduction to XML” title = “Introduction to XML” Logic expression means “does not have A” or “does not exist A” CLW ¬ A; 3. GLASSour graphical query language3.8.2 Negation  the use of Condition Logic Window QUERY: display the name of those members who haven’t written the publication titled “Introduction to XML”. DASFAA2003, Kyoto, Japan

  30. member member : A : : B : Path identifier “$pro” represents the project element with its the attributes and/or simple subelements publication publication : $pro : project name title = “Introduction to XML” title = “Introduction to Internet” With the statement in CLW, the information of the projects will be extracted only when condition A is satisfied. CLW A  B; {IF (A) THENEXTRACT $pro;} 3. GLASSour graphical query language3.8.3 IF-THEN Statement Query: Display the members with their names who have written a publication titled “Introduction to XML” or “Introduction to Internet”; and for those members who have written “Introduction to XML”, also display all information about the projects that they have taken part in. Without the statements in CLW, the information of the projects that all satisfied members have taken part in will be displayed. DASFAA2003, Kyoto, Japan

  31. 4. Related works and comparison • Form-based graphical XML query languages have a limited expression power. • Graphical XML Query Language [15] • XMLApe Query Language [17] • XML-GL[4,5] is not strong in expressing query logic and may cause misunderstanding in some cases. Ref[4]S. Ceri, S. Comai, E. Damiani, P, Fraternali, S. Paraboschi, and L. Tanca. XML-GL: a graphical language of querying and restructuring XML documents. In Proc. WWW8, Toronto, Canada, May 1999 Ref[5] S. Ceri, S. Comai, E. Damiani, P. Fraternali, and L. Tanca. Complex Queries in XML-GL. SAC (2) 2000: 888-893 Ref[15] Leo Mark, etc. XMLApe. College of Computing, Georgia Institue of Technology. http://www.cc.gatech.edu/projects/XMLApe/ Ref[17]JanParedaens, PeterPeelman, LetiziaTanca. G-Log: A Graph-Based Query Language. IEEE Transactions on Knowledge and Data Engineering, 7(3):436--453, June 1995. DASFAA2003, Kyoto, Japan

  32. 4. Related works and comparisonFeatures of XML-GL • XML-GL is the world’s first visual language that explicitly addresses the full complexity of querying XML data. • Has a bipartite structure to express querying and restructuring. • Supports various XML queries • Selection and projection • Join from one or more input documents; • Construction of new documents and new elements • Arithmetic and aggregate functions • Union, difference, heterogeneous union, and Cartesian product. DASFAA2003, Kyoto, Japan

  33. 4. Related works and comparisonAn example of XML-GL The second interpretation: For all <manufacturer> elements where rank <= 10, we output MN-NAME, YEAR and <model> subelement with MO-NAME and RANK; and for all <manufacturer> elements we output MN-NAME and YEAR again but do not output <model> subelement. (Some <manufacturer>s will appear twice in the result.) The first interpretation: For all <manufacturer> elements where rank <= 10, we output MN-NAME, YEAR and <model> subelement with MO-NAME and RANK; and for the remaining, we only output MN-NAME and YEAR. (No <manufacturer> will appear twice in the result; and all <manufacturer>s are output together in original order.) DASFAA2003, Kyoto, Japan

  34. Without any links with the entities in the LHS, all <MANUFACTURE>s are directly extracted from the data. MANUFACTURER MODEL With this link between two <MODEL>s, only the <MODEL>s with RANK <= 10 appear in the results. RANK <= 10 MANUFACTURER MODEL MN-NAME YEAR MO-NAME RANK 4. Related works and comparisonHow we express both(the 1st interpretation) For all <manufacturer> elements where rank <= 10, we output MN-NAME, YEAR and <model> subelement with MO-NAME and RANK; and for the remaining, we only output MN-NAME and YEAR.. (No <manufacturer> will appear twice in the output; and all <manufacturer>s are output together in original order) DASFAA2003, Kyoto, Japan

  35. The link between the two MANUFACTURERs implies only the MANUFACTURER that satisfies the condition in the LHS will be displayed. MANUFACTURER MANUFACTURER MODEL MODEL MN-NAME YEAR In comparison, the MANUFACTURER without any links with the LHS means all MANUFACTURER elements from the source data. RANK <= 10 MO-NAME RANK With this link, only <model>s with rank <=10 are kept in the outputs MANUFACTURER MN-NAME YEAR 4. Related works and comparisonHow we express both(the 2nd interpretation) For all <manufacturer> elements where rank <= 10, we output MN-NAME, YEAR and <model> subelement with MO-NAME and RANK; and for all <manufacturer> elements we output MN-NAME and YEAR again but do not output <model> subelement. (The results of both queries are put separately in one file.) DASFAA2003, Kyoto, Japan

  36. 4. Related works and comparisonComparison DASFAA2003, Kyoto, Japan

  37. 4. Related works and comparisonComparison (Cont.) DASFAA2003, Kyoto, Japan

  38. 5. Conclusion • Query logic can be explicitly expressed in CLW. • In comparison with XML-GL, GLASS can express negation and logic among conditions easily and clearly. • By separating logic expressions from graphical data structures, we now can build a clear and concise graphical query language. DASFAA2003, Kyoto, Japan

  39. 5. Conclusion (Cont.) • We tend to express the complexity of XML queries in XQuery standard including Aggregation functions and Negation. • We support view transformation and validation, especially swapping elements in different levels. [6] Ref[6]: Yabing Chen, Tok Wang Ling, Mong Li Lee: Designing Valid XML Views. To appear in the proceedings of 21st International Conference on Conceptual Modeling (ER'2002), October 7-11, 2002, Tampere, Finland. DASFAA2003, Kyoto, Japan

  40. Future work • Enhance the language; • Interpret the graphical expression into XQuery standard; • Expand the content of GLASS • data manipulation (e.g., INSERT, etc) • data integration • view definition • view maintenance DASFAA2003, Kyoto, Japan

  41. References [1] S. Abiteboul, D. Quass, J. McHugh, J. Widom and J. Wiener. The Lorel Query Language for Semistructured Data. Department of Computer Science, Stanford University. International Journal on Digital Libraries, 1(1):68-88, Apr. 1997. [2] M. Angelaccio, T. Catarci, and G. Santucci. QDB*: A graphical query language with recursion. IEEE Transactions on Software Engineering, 16(10):1150-1163, 1990. [3] T. Catarci, S.K. Chang, M.F. Costabile, S. Levialdi, and G. Santucci. A graph-based framework for multiparadigmatic visual access to databases. IEEE Transactions on Knowledge and Data Engineering, 8(3):455-475, 1996. [4]S. Ceri, S. Comai, E. Damiani, P, Fraternali, S. Paraboschi, and L. Tanca. XML-GL: a graphical language of querying and restructuring XML documents. In Proc. WWW8, Toronto, Canada, May 1999 [5] S. Ceri, S. Comai, E. Damiani, P. Fraternali, and L. Tanca. Complex Queries in XML-GL. SAC (2) 2000: 888-893 [6] Yabing Chen, Tok Wang Ling, Mong Li Lee: Designing Valid XML Views. To appear in the proceedings of 21st International Conference on Conceptual Modeling (ER'2002), October 7-11, 2002, Tampere, Finland. [7] Zhuo Chen. Extracting Schema from XML Documents. SoC, NUS. Honours Year Project Report. [8] Sara Comai, Ernesto Damiani, Letizia Tanca. The WG-Log System: Data Model and Semantics. INTERDATA technical report, T2-R06, July 1998. [9] C. J. Date. An Introduction to Database Systems. 3rd Edition, Addison-Wesley Publishing Company, 1981. [10]Gillian Dobbie, Wu Xiaoying, Tok Wang Ling, Mong Li Lee: ORA-SS: An Object-Relationship-Attribute Model for Semistructured Data. TR21/00, Technical Report, Department of Computer Science, National University of Singapore, December 2000. DASFAA2003, Kyoto, Japan

  42. References (Cont.) [11] P.W. Eklund, J. Leane, and C. Nowak. GrIT: An implementation of a graphical user interface for conceptual structures. Technical Report TR94-03, Computer Science Department, The University of Adelaide, February 1994. [12] Extensible Stylesheet Language (XSL) Specification. W3C Working Draft. Apr 1999. http://www.w3.org/TR/1999/WD-xsl-19990421/ [13]Ankur Gupta, Zahid Khan. Graphical XML Query Language. Course paper. College of Computing, Georgia Institute of Technology, Sep 2000 [14]Joshua S. Hodas, Robert M. Keller, Ingo Muschenets, Jeffrey Polakow, Amy R. Ward and Will Ballard. Condor: A Simple, Expressive Graphical Database Query Language. Department of Computer Science, Harvey Mudd College. Computer Science Technical Report HMC-CS-97-04. [15] Leo Mark, etc. XMLApe. College of Computing, Georgia Institue of Technology. http://www.cc.gatech.edu/projects/XMLApe/ [16] Yuanying Mo, Tok Wang Ling. Storing and Maintaining Semistructured Data Efficiently in an Object-Relational Database. Research Report. SoC, NUS. [17]JanParedaens, PeterPeelman, LetiziaTanca. G-Log: A Graph-Based Query Language. IEEE Transactions on Knowledge and Data Engineering, 7(3):436--453, June 1995. [18] Jayavel Shanmugasundaram, Kristin Tufte, Gang He, Chun Zhang, David DeWitt and Jeffrey Naughton. Relational Databases for Querying XML Documents: Limitations and Opportunities. VLDB 1999: 302-314 Department of Computer Sciences, University of Wisconsin-Madison. [19]XML Path Language (XPath) 2.0. W3C. Apr 2002. http://www.w3.org/TR/xpath20/ DASFAA2003, Kyoto, Japan

  43. References (Cont.) [20] XML Query Requirements. W3C. Feb 2001. http://www.w3.org/TR/xmlquery-req [21] XML Syntax for XQuery 1.0 (XQueryX). W3C. Jun 2001.http://www.w3.org/TR/xqueryx [22] XQuery 1.0 and XPath 2.0 Data Model. W3C. Apr 2002. http://www.w3.org/TR/query-datamodel/ [23] XQuery 1.0 and XPath 2.0 Functions and Operators Version 1.0. W3C. Apr 2002. http://www.w3.org/TR/xquery-operators/ [24]XQuery 1.0 Formal Semantics. W3C. Mar 2002.http://www.w3.org/TR/query-semantics/ DASFAA2003, Kyoto, Japan

  44. The End Thank you very much DASFAA2003, Kyoto, Japan

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