Service Automation in Semantic Web, EB and Grid

1
Service Automation in Semantic Web, EB and Grid

• Ching-Long Yeh ???
• Department of Computer Science and Engineering
• Tatung University
• Taipei, Taiwan
• Email chingyeh_at_cse.ttu.edu.tw
• http//www.cse.ttu.edu.tw/chingyeh

2
Content

• Web technology evolution
• Semantic Web
• Semantic Web Service
• Electronic Business Architecture ebXML
• Workflow Automation in Grid
• Semantic Web Service Architecture
• Summary

3
Web Technology Evolution
4
Web Technology

• HTML
• XML
• Electronic Business
• Semantic Web

5
WWW
Information Pool
Application
Client
Web server
URL
HTML Document
HTTP

• HTTP (Hyper Text Transport Protocol)
• HTML (Hyper Text Markup Language)
• URL (Uniform Resource Locator)

• Human-to-machine interaction
• Information explosion

6
Interaction Using XML
Information Pool
Information Pool
Application
Application
SOAP server
SOAP server
XML Document
XML Document
HTTP

• XML (eXtensible Markup Language)
• SOAP (Simple Object Access Protocol)

• Machine-to-machine interaction
• Service automation

7
Web Service Architecture
8
Electronic Business

• Application-to-Application
• Business Process Automation
• RosettaNet
• ebXML

Company B
Company A
ERP
ERP
9
Semantic Web

• The Semantic Web is a vision

the idea of having data on the web defined and
linked in a way that it can be used by machines
not just for display purposes, but for
automation, integration and reuse of data across
various applications

• See W3C Semantic Web Activity, by Marja-Riitta
  Koivunen, for more descriptions.

10
Semantic Web

• The Semantic Web is the new generation of the
  World Wide Web, based on the semantic network
  knowledge representation formalism, which enables
  packaging information in the form of
  object-attribute-value statements, so called
  triplets.
• By assuming that terms used in these statements
  are based on the formally specified meaning (for
  the community of interest), i.e. ontologies,
  these triplets can be semantically processed by
  machine agents.

From http//www2002.org/CDROM/poster/130.pdf
11
The Semantic Web Layered Architecture
Trust
Sig
Proof
Tim Berners-Lee Axioms, Architecture and
Aspirations W3C all-working group plenary
Meeting 28 February 2001
Logic
Rules
Ontology
RDF Schema
(http//www.w3.org/2001/Talks/0228-tbl/slide5-0.ht
ml)
RDF MS
XML Schema
XML
Namespaces
URI
Unicode
12
The Big Picture of SW
(http//semanticweb.org/about.htmlbigpicture)
13
What Is in an Ontology?

• One widely cited definition of an ontology is
  Grubers Gruber 1993 A specification of a
  conceptualization.
• An ontology is a formal explicit description of
• concepts in a domain of discourse (classes
  (sometimes called concepts)),
• properties of each concept describing various
  features and attributes of the concept (slots
  (sometimes called roles or properties)), and
• restrictions on slots (facets (sometimes called
  role restrictions)).
• An ontology together with a set of individual
  instances of classes constitutes a knowledge
  base.

14
Ontology Spectrum
(From http//www.ksl.stanford.edu/people/dlm/pape
rs/ontologies-come-of-age-mit-press-(with-citation
).htm)
15
Semantic Web Languages
16
What is XML?

• Extensible Markup Language
• A Syntax for Documents
• A Meta-Markup Language
• A Structural and Semantic Language, not a
  Formatting Language
• Not just for Web pages

17
XML Standards

• DTD
• Namespace
• Schema
• DOM
• CSS, XSL-T, XSL-FO
• XLink
• XPointer

18
XML Protocol SOAP
19
RDF MS

• RDF (Resource Description Framework)
• Beyond Machine readable to Machine understandable
• RDF consists of two parts
• RDF Model (a set of triples)
• RDF Syntax (different XML serialization syntaxes)
• RDF Schema for definition of Vocabularies (simple
  Ontologies) for RDF (and in RDF)

20
RDF Data Model

• Resources
• A resource is a thing you talk about (can
  reference)
• Resources have URIs
• RDF definitions are themselves Resources
  (linkage, see requirement 1)
• Properties
• slots, define relationships to other resources or
  atomic values
• Statements
• Resource has Property with Value
• (Values can be resources or atomic XML data)
• Similar to Frame Systems

21
A Simple Example

• Statement
• Ora Lassila is the creator of the resource
  http//www.w3.org/Home/Lassila
• Structure
• Resource (subject) http//www.w3.org/Home/Las
  sila
• Property (predicate) http//www.schema.org/Cre
  ator
• Value (object) "Ora Lassila
• Directed graph

sCreator
http//www.w3.org/Home/Lassila
22
OWLW3C Web Ontology Language

• OWL provides three increasingly expressive
  sublanguages OWL Lite, OWL DL, and OWL Full.

23
OWLW3C Web Ontology Language
OWL Lite language constructs
RDF Schema Features Class rdfProperty
rdfssubClassOf rdfssubPropertyOf rdfsdomain
rdfsrange Individual
(In)Equality equivalentClass equivalentProperty
sameAs differentFrom allDifferent
Property Characteristics inverseOf
TransitiveProperty SymmetricProperty
FunctionalProperty InverseFunctionalProperty
Property Type Restrictions allValuesFrom
someValuesFrom
Restricted Cardinality minCardinality (only 0
or 1) maxCardinality (only 0 or 1) cardinality
(only 0 or 1)
Header Information ontology imports
24
Semantic Web Services
25
Some Motivating Tasks

• The kinds of task we expect OWL-S to enable
• Automatic Web service discovery
• Automatic Web service invocation
• Automatic Web service composition and
  interoperation
• Automatic Web service execution monitoring

26
High-level View of the Service Ontology
Service
Resource
provides
presents
supports
describedBy
ServiceProfile
ServiceGrounding
What the service does
How to Access it
ServiceModel
How it works
27
Top Level of the Process Ontology
Input Precondition Output effect
hasProcess hasProfile
Process
Profile
Condition
Atomic Process
has Grounding
computedInput computedOutput computedEffect comput
edPrecondition invocab
Composite Process
expand collapse
realizes realizedBy
Simple Process
compsedBy
Control Construct
Sequence
Repeat Until
28
Grounding a Service to a Concrete Realization
OWL-S
DL-Based Types
Process Model
Inputs/Outputs
Atomic Process
Message
Operation
Binding to SOAP, HTTP, etc.
WSDL
29
Electronic Business Architecture
30
The ebXML Framework at Work
31
Components of the ebXML Framework

• Defining how public business-process must be
  described using the ebXML BPSS standard.
• Defining the semantics of business documents that
  are exchanged in public processes using ebXMLs
  Core Component (ebCC) standard.
• Definition of services and the constraints in
  using the services using Collaboration Protocol
  Profile (CPP) defined in the ebXML CPPA standard.
• Description of the mutual agreement between the
  business partners Collaboration Protocol
  Agreement (CPA) to carry out the public
  business process. The schema for a CPA is also
  defined by ebXML CPPA standard.
• Protocols for registering, storing, and
  retrieving public business processes and
  associated business documents, and CPPs using the
  ebXML Registry standard.
• A standard way to send and receive messages
  between business partners, as defined in the
  ebXML Message specification.

32
Workflow Automation in Grid
33
Introduction

• Grid technologies are changing the way scientists
  conduct research, fostering large-scale
  collaborative endeavors where scientists share
  their resources, data, applications, and
  knowledge to pursue common goals.
• Collaborations,
• Virtual Organizations (VOs), LIGO and GEO
• Virtual Data, first introduced within the GriPhyN
  project,
• The Grid applications are no longer monolithic
  codes, rather they are being built from existing
  application components.
• In general, we can think of applications as being
  defined by workflows, where the activities in the
  workflow are individual application components
  and the dependencies between the activities
  reflect the data and/or control flow dependencies
  between the components.

34
(No Transcript)
35
Introduction

• Although Grid middleware allows for discovery of
  the available resources and of the locations of
  the replicated data, users are currently
  responsible for carrying out all of these steps
  manually.
• Automating this process is desirable and
  necessary because of
• Usability
• Complexity
• Solution cost
• Global cost
• Reliability

36
A knowledge-based architecture for workflow
generation on the Grid
37
Architecture of the planning system and
its interactions with other Grid-based services.
38
Application Example

• The GriPhyN Virtual Data System (VDS) that
  consists of Chimera, Pegasus and DAGMan has been
  used to execute both large workflows with an
  order of 100,000 jobs with relatively short
  runtimes and workflows with small number of
  long-running jobs.

Components of a Workflow Generation, Mapping and
Execution System.
39
Application Example
A simple example of partial workflow descriptions
expressed in Chimeras Virtual Data Language (VDL)
40
Application Example
Abstract workflow produced by Chimera
41
Semantic Web Services Architecture
42
Introduction

• Develop architectural and protocol abstractions
  forming a reference architecture to support
  Semantic Web Service technologies
• The support functions the architecture will cover
• Dynamic Service Discovery
• Service Process Enactment and Management
• Negotiation and Contracting
• Semantic Web Community Support Services
• Semantic Web Service Lifecycle and Resource
  Management Services
• Cross-cutting Issues

43
Introduction

• Semantic Web Services are viewed as a way to
  extend the capabilities of web services in the
  direction of dynamic interoperability.
• Commercial web services, in both B2B and B2C
  applications
• Grid computing
• Ubiquitous computing
• Information Services

44
Functional Areas
45
Functional Areas
46
Functional Areas
47
Functional Areas
48
Functional Areas
49
Summary

• Abstractions of services on emerging
  technological architectures
• The Semantic Web Service Architecture is probably
  an integration of the abstractions of services
  for various functional areas.

50
References

• W3C Semantic Web Activity, http//www.w3.org/2001/
  sw/
• Semantic Web Specifications, http//www.w3.org/200
  1/sw/spec
• N. F. Noy and D. L. McGuinness. Ontology
  development 101 a guide to creating your first
  ontology''. Stanford Knowledge Systems Laboratory
  Technical Report KSL-01-05 and Stanford Medical
  Informatics Technical Report SMI-2001-0880, March
  2001.
• D. L. McGuinness. "Ontologies come of age". In D.
  Fensel, J. Hendler, H. Lieberman, and W. Wahlster
  (eds.) Spinning the Semantic Web Bringing the
  World Wide Web to Its Full Potential. MIT Press,
  2002.
• ebXML Technical Architecture Project Team, ebXML
  Technical Architecture Specification v1.0.4,
  http//www.ebxml.org/specs/ebTA.pdf
• J. Blythe, E. Deelman, and Y. Gil, Automatically
  composed Workflows for Grid Environments, IEEE
  INTELLIGENT SYSTEMS, July/August, 2004.
• Y. Gil, E. Deelman, J. Blythe, C. Kesselman, and
  H. Tangmunarunkit, Artificial intelligence and
  Grids workflow planning and beyond, IEEE
  INTELLIGENT SYSTEMS, Jan/Feb, 2004.
• E. Deelman, et al, "Pegasus mapping scientific
  workflows onto the Grid ," Across Grids
  Conference 2004, Nicosia, Cyprus, 2004.
• Mark Burstein (ed.), Semantic Web Services
  Architecture Requirements
• Version 1.0 (1 June 2004), http//www.daml.org/ser
  vices/swsa/swsa-requirements.html