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
2003-3-28
DASFAA2003, Kyoto, Japan
1
Roadmap
1.
2.
3.
4.
5.
Introduction and motivation
ORA-SS  the data model of our
language
GLASS, our graphical query language
Related works and comparison
Conclusion and future work
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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.
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1. Introduction and motivation
(Cont.)
 Criteria of a good query language
Expressiveness
 Completeness
 User-friendliness

 Graphical Query Language: user-friendly
and easy understanding
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2. ORA-SS
 the data model of our language
 ORA-SS (Object-Relationship-Attribute model for SemiStructured data) : a rich semantic data model.
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:
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>
2, 1:n, 1:1
course
name
cs, 2, 1:n, 1:n
student
code
title
number
The DTD of “Department.xml”
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<grade> belongs to the
binary relationship type
“cs” between <course>
and <student>
cs
name
grade
The ORA-SS schema diagram of
“Department.xml”
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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.
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3. GLASS  our graphical query language
3.1 General concepts in GLASS
1) Data icons
Rectangle: the object class in ORA-SS, non-terminal
element in XML (element with subelements or
attributes).
ii. Circle: the attribute in ORA-SS, terminal element
with PCDATA only and the attribute (or attribute list)
in XML.
i.
2) Connections
i. Arrow: relationship type
ii. Dashed arrow: IDREF in XML
iii. Line: link between output and original entities
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3. GLASS  our graphical query language
3.1 General concepts in GLASS (Cont.)
3) Box: the group entity in GLASS query graphs that
consists of all rectangles or circles inside the box.
4) Derived entities: derived object classes and attributes
are represented as dashed rectangles and dashed circles
which are new data types defined by users.
5) 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.
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3. GLASS  our graphical query language
3.1 General concepts in GLASS (Cont.)
6) Path Identifier


a unique name given to data icons or boxes;
indicated by prefix “$”.
7) Condition Identifier
a unique name given to the connections;

without prefix “$”.
8) Logic Expression: specifies the logic in query
conditions

9) Statement: helps construct complex outputs
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3. GLASS  our graphical query language
3.1 General concepts in GLASS (Cont.)
Structure of GLASS
query graph
Query
condition
Result
construction
CLW
Logic expressions and
statements
The black parts are optional.
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3. GLASS  our graphical query language
3.2 Output construction
Example 1:
<!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”
department
2, 1:n, 1:1
course
name
cs, 2, 1:n, 1:n
student
code
title
number
cs
name
<?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>
grade
The ORA-SS schema diagram of
“Department.xml”
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The content of “Department.xml”
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department
3. GLASS  our graphical query language
2, 1:n, 1:1
3.2 Output construction (Cont.)
(a) Extract courses and all information one level under
course elements by using the default output method
QUERY
QUERY RESULT
course
The default
entity type
implies both
attributes
and simple
subelements
of course
element
<course code=“201”>
<title>Software Engineering</title>
</course>
<course code=“303”>
<title>Database Design</title>
</course>
The default number of level is
“1”. We use “/2” to represent 2
levels under element course.
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In the default output
method, everything
will be kept in the
original style from
source data.
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course
name
cs, 2, 1:n, 1:n
student
code
title
number
cs
name
grade
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>
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department
3. GLASS  our graphical query language
2, 1:n, 1:1
3.2 Output construction (Cont.)
(b) Extract courses and all information at all levels under
course elements by using the default output method
QUERY
QUERY RESULT
course
*
“*” is a wildcard which
means all nested level
under course element.
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<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>
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course
name
cs, 2, 1:n, 1:n
student
code
title
number
cs
name
grade
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>
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department
3. GLASS  our graphical query language
2, 1:n, 1:1
3.2 Output construction (Cont.)
(c) Extract courses with all attributes of course element in
the original XML document
QUERY
QUERY RESULT
course
<course code=“201”></course>
<course code=“303”></course>
@
The circle with “@” inside implies
all attributes of course element in
the original XML document
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course
name
cs, 2, 1:n, 1:n
student
code
title
number
cs
name
grade
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>
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department
3. GLASS  our graphical query language
2, 1:n, 1:1
3.2 Output construction (Cont.)
(d) Extract courses and all subelements at one level under
course elements (except the attributes of course elements)
QUERY
QUERY RESULT
course
<course>
<title>Software Engineering</title>
</course>
<course>
<title>Database Design</title>
</course>
e
The circle with “e” inside indicates
all simple subelements of course
element.
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course
name
cs, 2, 1:n, 1:n
student
code
title
number
cs
name
grade
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>
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department
3. GLASS  our graphical query language
2, 1:n, 1:1
3.2 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.
QUERY
QUERY RESULT
course
The blank
circle implies
both
attributes
and simple
subelements
of course
element
The blank rectangle stands
for all complex
subelements of course
element.
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<course code=“201”>
<title>Software Engineering</title>
<student></student>
<student></student>
</course>
<course code=“303”>
<title>Database Design</title>
<student></student>
</course>
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.
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course
name
cs, 2, 1:n, 1:n
student
code
title
number
cs
name
grade
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>
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3. GLASS  our graphical query language
3.2 Output construction (Cont.)
(f) Extract courses with their titles as attributes and codes
as subelements in the output.
QUERY
QUERY RESULT
course
course
@
title
<course title=“Software Engineering”>
<code>201</code>
</course>
<course title=“Database Design”>
<code>303</code>
</course>
title
e
code
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.
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a demonstration of the
conversion between
attribute and
subelement
DASFAA2003, Kyoto, Japan
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>
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3. GLASS  our graphical query language
3.3 Basic query operators  Selection
To select all courses whose codes
begin with “2”, we can write an
XQuery language as:
course
course
*
FOR $c IN $department/course
WHERE $c/@code/data() = ‘2%’
RETURN $c
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code
= ‘2%’
The output course
in RHS is the
course that
satisfies the
condition in LHS
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3. GLASS  our graphical query language
3.4 Basic query operators  Projection
To project all courses with their
titles, XQuery will give the
following expression:
course
FOR $c IN $department/course
RETURN
<course>{ $c/title }</course>
title
Without the specification of
subelements or attributes, the
title will remain unchanged as
a subelement of course in the
result.
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3. GLASS  our graphical query language
3.5 Basic query operators  Join
Suppose we have another XML data named as “Description.xml”
containing the descriptions of all courses.
course
<!ELEMENT course (title?, description)>
<!ATTLIST course code ID #REQUIRED>
<!ELEMENT title PCDATA>
<!ELEMENT description PCDATA>
code
The DTD of “Description.xml”
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title
description
The ORA-SS schema diagram
of “Description.xml”
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3. GLASS  our graphical query language
3.5 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.
FROM Department.xml
FROM Description.xml
course
course
course
*
The URLs of
data sources
code
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description
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description
21
3. GLASS  our graphical query language
3.6 Aggregation functions  group & average
Query: For all courses, display courses with their information (in default way)
and the average grade of each course.
course
avg_grade is a derived
entity and it will be
constructed as a
subelement of “course”
course
_group
To group student
under course
student
e
avg_grade
cs
AVG
The character “e”
inside the dotted
circle implies the
avg_grade is a
element type
grade
Aggregation functions are
available after “_group”
functionality is done.
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3. GLASS  our graphical query language
3.6 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 in distinct-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>
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3. GLASS  our graphical query language
3.7 Query order sensitive data
Suppose we have an order sensitive data
“Bib.xml”.
The <author> order is
important to the <book>
Example 2:
book
2, +, +, <
author
isbn
title
content
firstname
lastname
The ORA-SS schema diagram of “Bib.xml”, order-sensitive data
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3. GLASS  our graphical query language
3.7 Query order sensitive data (Cont.)
Query: Display all books with their isbn’s, titles and their first authors .
book
[1]
author
isbn
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“[1]” means the first
element in order
title
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3. GLASS  our graphical query language
3.8 Advanced features of GLASS
Suppose we have a more complex XML data about projects,
members and publications.
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
The ORA-SS schema diagram of the data about “project, member
and publication”
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3. GLASS  our graphical query language
3.8.1 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”.
The box
member
member
_group
project
name
= ‘S%’
To group
publications
under each pair
of (member,
project)
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name
CNT < 5
_group
To group projects
under member
publication
CNT > 6
“CNT” means “count”.
(“CNT” do count
without eliminating
duplicates.) We can
also use other
aggregation functions
like SUM, AVG, etc.
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3. GLASS  our graphical query language
3.8.1 Group entity  the use of box (Cont.)
member
name
= ‘S%’
member
member
_group
_group
project
project
CNT < 5
name
name
= ‘S%’
_group
publication
CNT > 6
CNT < 5
_group
publication
Select publication GROUP
BY <member, project>
pairs
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”.
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member
name
Select publication only
GROUP BY <member>
CNT_UNIQUE > 6
CNT_UNIQUE will
eliminate duplicates in
counting.
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”.
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3. GLASS  our graphical query language
3.8.2 Negation  the use of
Condition Logic Window
QUERY: display the name of those members who haven’t written the publication
titled “Introduction to XML”.
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
title
= “Introduction to XML”
Logic expression
means “does not
have A” or “does
not exist A”
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with title = “Introduction to XML”
CLW
¬ A;
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3. GLASS  our graphical query language
3.8.3 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.
:A:
Path identifier “$pro” represents the
project element with its the attributes
and/or simple subelements
member
member
:B:
publication
publication
project
: $pro :
name
title
= “Introduction
to XML”
title
= “Introduction
to Internet”
CLW
A  B;
{IF (A) THEN EXTRACT $pro;}
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Without the
statements in CLW,
the information of
the projects that all
satisfied members
have taken part in
will be displayed.
With the statement in CLW, the
information of the projects will be
extracted only when condition A
is satisfied.
30
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] Jan Paredaens, Peter Peelman, Letizia Tanca. G-Log: A Graph-Based Query Language. IEEE Transactions on
Knowledge and Data Engineering, 7(3):436--453, June 1995.
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4. Related works and comparison
Features 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.
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4. Related works and comparison
An example of XML-GL
The first interpretation:
The second interpretation:
For all <manufacturer> elements
where rank <= 10, we output MN-NAME, YEAR and
<model> subelement with MO-NAME and RANK;
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.)
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.)
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33
4. Related works and comparison
How we express both (the 1st interpretation)
MANUFACTURER
MODEL
RANK
<= 10
Without any links with the
entities in the LHS, all
<MANUFACTURE>s are directly
extracted from the data.
MANUFACTURER
MNNAME
MODEL
YEAR
MONAME
RANK
With this link between two
<MODEL>s, only the
<MODEL>s with RANK <= 10
appear in the results.
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)
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4. Related works and comparison
How we express both (the 2nd interpretation)
The link between
the two
MANUFACTURERs
implies only the
MANUFACTURER
that satisfies the
condition in the
LHS will be
displayed.
MANUFACTURER
MODEL
MANUFACTURER
MNNAME
MODEL
YEAR
RANK <= 10
MANUFACTURER
MONAME
With this link, only
<model>s with rank <=10
are kept in the outputs
RANK
MNNAME
YEAR
In comparison, the
MANUFACTURER without
any links with the LHS
means all MANUFACTURER
elements from the source
data.
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.)
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4. Related works and comparison
Comparison
Data Model
Support Selection,
Projection
and Join
XML-GL
Graphical XML
Query Language
XMLApe Query
Language
GLASS
XML DTD
XML DTD
XML Schema
ORA-SS
Yes
Yes
Yes
Yes
Support Queries on
Ordered Data
Yes
No
No
Yes
Support “group by”
operator
Yes
No
No
Yes
Support Aggregation
Function
Yes
No
No
Support Negation
No
No
No
Yes
Support Complex
Condition
Yes
No
No
Yes
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4. Related works and comparison
Comparison (Cont.)
XML-GL
Graphical XML
Query Language
XMLApe Query
Language
GLASS
Support XPath
Yes
No
No
Yes
Support Qualifiers(,
)
No
No
No
Yes
No
No
No
Yes
Support User-defined
View
Yes
No
No
Yes
Support View
Validation
No
No
No
Yes
Support Conditional
Output Construction
(e.g. With IF-THEN
Clause)
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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.
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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.
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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

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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.
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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] Jan Paredaens, Peter Peelman, Letizia Tanca. 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/
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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/xqueryoperators/
[24] XQuery 1.0 Formal Semantics. W3C. Mar 2002.http://www.w3.org/TR/query-semantics/
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The End
Thank you very much
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