Automatic Creation of Web Services from Extraction Ontologies

1
Automatic Creation of Web Services from
Extraction Ontologies

• Cui Tao, Yihong Ding, and Deryle Lonsdale
• Brigham Young University

1st International Workshop on Semantic Web
Applications Theory and Practice (SemWAT 2006)
in affiliation with ER 2006, Tucson, Arizona,
November 2006
2
Motivation

• Semantic Web
• Machine-understandable
• Ontology formal specification of
  conceptualizations
• Web services
• Convention descriptions for mapping knowledge
  into and out of Web application programs
• Machine-executable
• Normally not machine-understandable
• Can Semantic Web technologies help in creating
  machine-understandable (semantic) web services?

3
Current Solution Web Service Annotation
Annotation
(3) Web service annotation
4
Alternate Solution Can we do better?
Ontology-based generation
Semantic Web Services
(2) Web service creation
5
Direct Semantic Web Service Generation from
Ontologies
Ontology
Atomic Semantic Web Services
compose
compile
generate
Complex Semantic Web Service
6
Data-Extraction Ontologies

• Semantically equivalent to OWL ontologies
• Object sets --- Classes
• Relationship sets --- Properties
• Constraints --- Restrictions
• Data frames unique ontology components
• Formal specifications of data recognition
  patterns
• Executable for data extraction

7
Example car-ad ontology (Graphical)
8
Example car-ad ontology (OSM-L)
Car -gtobject Car 0..1 has Year 1.. Car
0..1 has Make 1.. Car 0..1 has Mileage
1.. Car 0.. has Feature 1.. Car 0..1
has Price 1.. PhoneNr 1.. is for Car
0.. Year matches 4 constant extract
\d2 context
"(\\d)4-9\d,\d"
substitute "" -gt "19" , End
9
Two-stage Semantic Web Service Creation

• From extraction ontologies to Java APIs
• From Java APIs to semantic web services

10
From Extraction Ontologies to Java APIs

• OSM-L parsing
• Symbol table creation
• Java code generation

11
Java Code Generation

• Concepts ? Java interfaces
• Multiple inheritance
• Implemented classes
• Executable methods
• Others ? Java classes
• Specific fields and methods
• E.g. binary relationship
• Fields two concepts and constraints
• Method checkConstraint

12
From Java APIs to Semantic Web Services

• Atomic data recognition web service
• Each lexical ontology concept
• Method recognize() string
• Generate in a straightforward manner
• Several available tools such as GLUE
  (http//www.themindelectric.com)
• Automatically created WSDL descriptions
• Semantic web services

13
Semantic WSDL
14
Simple Semantic Service Composition

• Binary relationship service extraction
• Two atomic concept extraction services one
  binary relation constraint checking service
• E.g. a complex service extracting car-price
  pairs
• Car instance extraction service
• Price instance extraction service
• checkConstraint(car-price)

15
Generic Web Service Composition

• Logic rules derived from ontologies can be
  straightforwardly composed
• Checking existence
• Extracting instances
• Comparing values
• Checking constraints
• Future work Can we convert any human request to
  logic rules based on ontologies?

16
Conclusion

• Semantic web service creation is a crucial
  problem in current Semantic Web and web service
  research
• We present a novel two-stage Semantic Web service
  generation paradigm
• From extraction ontologies to Java APIs
• From Java APIs to web services
• Uniqueness of our approach
• Avoids service annotation
• Facilitates complex service composition

17
OSM-L Parsing (27 grammars)
26
7
18
Symbol Table (e.g. data-frame ST)

• Data Frame
• Constant block(1)
• Lexicon block(01)
• Keyword block(01)

ConstantElement block (1)

• Extract Pattern (1)
• Context Pattern (01)
• Except Pattern (01)
• Filter Pattern (01)
• Substitute Pattern (01)

• extract-type,
• context-type,
• except-type,
• filter-type,
• substitute-type,
• keyword-type,
• lexicon-type

Pattern Regular expression Case tag
Pattern type