IBM © Copyright IBM Corporation 2006 Guo Tong Xie ( ) [email protected] Semantic Integration, IBM China Research Lab Semantic Web Applications ABC

IBM中国研究院

© Copyright IBM Corporation 2006

Guo Tong Xie (谢国彤 )[email protected] Integration, IBM China Research Lab

Semantic Web Applications ABC

IBM中国研究院


Agenda

Session A- Semantic Web Revisit- Semantic Wiki- Semantic Information Management

Session B- What you know about semantic web applications- Semantic Information Retrieval- Semantic Web Services

Session C- Semantic Web Enabled Software Engineering- What semantic web applications you want to develop- Sample Application Scenarios

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Objective

Learn what Semantic Web applications are developed Learn how Semantic Web applications are developed Think what Semantic Web applications you will develop

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Agenda


Session B- what you know about semantic web applications- Semantic Information Retrieval- Semantic Web Services


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Semantic Web Revisit – A web of meaningful data

Web Nature of Semantic Web - RDF- Everything is resource, with a global URI

http://www.research.ibm.com/people/x/xieguot

- Resources are linked via triples, <subject, predicate, object> <http://www.research.ibm.com/people/x/xieguot, rdfs:type, foaf:Person> <http://www.research.ibm.com/people/x/xieguot, foaf:workInfoHomepage, http://www.researc

h.ibm.com> <http://www.research.ibm.com/people/x/xieguot, foaf:mbox, [email protected]>

- Ontology is defined in a decentralized way – import, link and redefine

Semantic Nature of Semantic Web – Ontology- Resources can have types- A type can have sub-types and complex restrictions- Resources can have properties- A property can have sub-properties and complex restrictions- Rules

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Semantic Wiki – Motivation

Consistency of content: The same information often occurs on many pages. How can one ensure that information in different parts of the system is consistent, especially as it can be changed in a distributed way?

Accessing knowledge: Large wikis have thousands of pages. Finding and comparing information from different pages is a challenging and time-consuming task.

Reusing knowledge: Many wikis are driven by the wish to make information accessible to many people. But the rigid, text-based content of classical wikis can only be used by reading pages in a browser or similar application.

Typical Wiki

Semantic Wiki

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Semantic Wiki – Approach

Key Points- Data in wiki-article can be annotated with type.- Typed data can be connected via typed link.- Everybody can create any relation or attribute.

Key Components- RDF Triple Store- SPARQL Query Engine- RDF Feed

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Semantic Wiki – Applications in ISWC2006

OntoWiki - A Tool for Social, Semantic Collaboration Semantic MediaWiki

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Selected Application – Semantic Wikipedia

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Non-semantic Version

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Semantic Version

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From Links to Typed Links

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From Values to Attributes

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What Humans See – View as HTML

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What Machines See – View as RDF

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Benefits of Semantic Wikipedia – Create Articles by Querying

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Benefits of Semantic Wikipedia – Reason and Integrate Facts

Property characteristic reasoning- “PC member of” inverseOf “Has PC member”

Web style data integration- Integrated “Has PC member”

Individual “PC member of” data

Integrated “Has PC member” data

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Semantic Information Management – Motivation

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Semantic Information Management – Approaches

Revolution – Transform Everything to RDF- Functionally rich (reasoning, query)- High cost (storage, synchronization)

Evolution – Map Everything to Ontology- Keep original system running- Complex mapping, query rewriting

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Semantic Information Management – Applications in ISWC2006

Bioinformatics- From Legacy Relational Databases to the Semantic Web: an In-Use Application for T

raditional Chinese Medicine- Enabling an Onlince Community for Sharing Oral Medicine Cases Using Semantice

Web Technologies- Active Semantic Electronic Medical Record- Towards Semantic Interoperability in a Clinical Trials Management System

Science- Semantically-Enabled Large-Scale Science Data Repositories

Personal Information Management (PIM)- Semantic Desktop 2.0: The Gnowsis Experience

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Selected Application – Semantic Desktop

Sesame2 – central RDF repository PIMO store handles the information in

the user’s Personal Information Model Aperture crawlers generate RDF data

by crawling original data source, file system and email etc.

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PIMO Ontology Modeling Layer

PIMO-Basic: defines the basic language constructs.

PIMO-Upper: A domain-independent ontology defining abstract sub-classes of Thing.

PIMO-Mid: More concrete sub-classes of upper-classes. The PIMO mid-level ontology serves to integrate various domain ontologies and provides classes for Person, Project, Company

Domain ontologies: A set of domain ontologies where each describes a concrete domain of interest of the user.

PIMO-User: the extensions of above models created by an individual for personal use.

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Selected Application – Dartgrid

Ontology Service is used to expose the shared ontologies that are defined using web ontology languages.

Semantic Registration Service maintains the semantic mapping information.

Semantic Query Service is used to process SPARQL semantic queries.

Search Service supports full-text search in all databases.

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Map Database to Ontology

LAV mapping

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Dynamic Semantic Query Portal

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Semantic Navigation

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Intuitive Search Portal

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Agenda




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what you know about semantic web applications

Inputs from SJTU students:- Cao ying chun, pervasive computing, MIT, pigviewer- Si pin chao, dynamic view, Southeast University

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Semantic Information Retrieval – Motivation

Motivation- Traditional IR has reached a plateau with the “bag of words” view of doc

uments- Additional information need be incorporated and utilized to boost result r

elevance Think of Google PageRank as adding linking information (a kind of i

mplicit voting) into IR Understand the “words” in the document better using information ext

raction techniques to identify entities the words refer to and the entities’ properties

These entities and properties are actually “semantic” information of the words and can be defined/described using ontologies.

- User’s information need / intention need be better expressed and understood

Using domain knowledge to guide the user Understand user intention with the help of domain knowledge Example: mSpace (HyperText 2005) , /facet, OntoGator (ISWC 200

6)

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Semantic Information Retrieval – Approaches

Using semantic technologies to help traditional IR Using traditional IR to help semantic query

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Using semantic technologies to help traditional IR

documents

Information extraction

and analysis engine

Domain ontology,Rules,Extraction templates

Semantically annotateddocuments

Richer query and search via

structured queries and

guided navigation

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Using traditional IR to help semantic query

Many different ways - Finding ontologies to reuse for a domain

E.g. Swoogle (http://swoogle.umbc.edu)- Adding flexibility to semantic query

When it’s hard to express a query strictly using semantic constructs for a general notion of “related to”, e.g. Professor AND “semantic web”

Implementation: treat an item in KB as a “virtual” document , extract text from KB for the item, and search them using IR.

E.g. An enhanced model for searching semantic portal (WWW 2005)- Improve query answering performance

Using IR inverted index to index semantic information and answer semantic queries

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Semantic Information Retrieval – Applications in ISWC2006

Understand Semantics of Words- NEWS: bringing Semantic Web Technologies into News Agencies

Understand Users’ Intention- Ontogator --- A Semantic View-Based Search Engine Service for Web Applications- Foafing the Music: Bridging the semantic gap in music recommendation- MultimediaN E-Culture demonstrator

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Selected Application – OntoText

UIMA (http://www.research.ibm.com/UIMA/) OntoText (http://www.ontotext.com/kim/index.html)

Semantic Search via XML Fragments: A high precision approach to IR (SIGIR 2006)

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Semantic Web Services – Motivation

Automatic Web Services discovery- Automatic Web services discovery is an

automated process for location of Web services that can provide a particular class of service capabilities, while adhering to some client-specified constraints.

Automatic Web Services invocation - Automatic Web services invocation is the

automatic invocation of an Web services by a computer program or agent, given only a declarative description of that service, as opposed to when the agent has been pre-programmed to be able to call that particular service.

Automatic Web Services composition and interoperation - This task involves the automatic selection,

composition, and interoperation of Web services to perform some complex task, given a high-level description of an objective.

DB

DB

Network

Sales

Ordering Billing

Accounting

ProvisioningManageTraffic

ControlElements

CollectEvents

configurationnet event

eventselement configuration

usage

revenuecommercial order

service order

Sales

Ordering Billing

Accounting

ProvisioningManageTraffic

ControlElements

CollectEvents


usage


service order

net eventconfiguration

Product A"Silo" Monolith

Product B"Silo" Monolith

SwivelChair

Ente

rprise

Data

Sto

re

Customer Space

Network Space Network

Ente

rprise

Data

Sales

Ordering Billing

Accounting

ProvisioningExtract Billable

Events

ControlElements

CollectEvents

configuration net event


usage


service order

ManageTraffic

Finances &Business

Tele

co

m O

SS

/BS

SNetworkspecific

Productspecific

Businesssystems

customizedsolution

standardimpementation

Internet

- 1500 systems in silos; only 500 interconnected.- 500 “connected systems” create over 2000 interfaces.

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Semantic Web Services – Approach

WSDL-S OWL-S WSMO SWSF

WSDL-S OWL-S

http://www.w3.org/2002/ws/swsig/

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Semantic Web Services – Applications in ISWC2006

Service Discovery- RS2D: Fast Adaptive Search for Semantic Web Services in Unstructured P2P

Networks

Service Composition- A Constraint-Based Approach to Horizontal Web Service Composition- A Formal Model for Semantic Web Service Composition- Web Service Composition Via Generic Procedures and Customizing User

Preferences- A Mixed Initiative Semantic Web Framework for Process Composition- IRS-III: A Broker for Semantic Web Services Based Applications

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Selected Application - Creole

Service Metadata Workbench

High level Business Process ModelModeler Development

Platform

Executable BusinessProcess Model

Business Analyst Developer

Runtime

Runtime Quality of Service Considerations

Unavailable Switch to a different service

Legacy and packaged apps New application

developmentNew Business Partners

Service AnnotationService DiscoveryAutomatic Service

Composition

Service AnnotationService DiscoveryAutomatic Service

Composition

Service DiscoveryLegacy AdaptationAutomatic Service

CompositionAdapter Generation

Service DiscoveryLegacy AdaptationAutomatic Service

CompositionAdapter Generation

Flexible Robust Runtime via

Dynamic Discovery & Binding

Flexible Robust Runtime via

Dynamic Discovery & Binding

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Purchase Order Placement: An Example

Can be discovered and mapped at build time 1000’s of suppliers ->

discover and map at run time

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Check Availability: Mapping

ACME Inc.Check Inventory

UPC

DeliveryDate

Quantity

Yes/No

XYZ Inc.

FindItemAvailabilityEANCodeDueDate

NumItemsYes/No

Check AvailabilityPartNum

Date

Qty

Yes/No

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Semantics can help disambiguate

EANCodeEANCode

UPC

UPC Version A UPC Version E

EANCodeEAN 8

EANCodeEAN 13

subClassOf

type type

type

type

EANCodePartNumber

subClassOf

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Request ACME Inc.

Signed&EncryptedOrderDocument Purchase Order

Processor Service

Order ConfirmationDocument

DigitalSigning Service

Encryption Service

OrderDocument

SignedDocument

Plain TextDocument

is an instanceOf

Semantic Web Service Composition using AI Planning

OrderDocument

Order ConfirmationDocument

input

output

Service Composition

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Agenda




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Semantic Enabled Software Engineering - Motivation

MDA- No formal semantics and reasoning engine- Software design and development are

becoming more and more complicated- No good collaboration mechanism other than

CVS- No good reuse of modeling artifacts- No formal reuse of know-how of experts

Semantic Web- No industry strength software engineering

methodology and tool- No connection with typical software design

and development- Lack of experienced designers and

developers

PIM

PSM ・・・PSMPSM

业务要件

每个平台的映射

实现的映射

实现・・・实现实现

业务领域的分析･建模

CIM

业务系统的分析･设计标准模型

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Semantic Enabled Software Engineering - Approaches

How can MDA help Semantic Web?- Modeling and Interoperability (MOF, UML, XMI)- Transformation (QVT)- Methodology

How can Semantic Web help MDA?- Formal semantics and reasoning- Web nature

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Semantic Enabled Software Engineering – Applications in ISWC2006

A Model Driven Approach for Building OWL DL and OWL Full Ontologies

2nd International Workshop on Semantic Web Enabled Software Engineering (SWESE 2006)

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Selected Application – Ontology Definition Metamodel

A standard MOF2 compliant metamodel for Ontology Definition (ODM) based on W3C Web Ontology Language (OWL) specification

Mappings between ODM and other modeling languages, including UML2, Common Logic and Topic Map

A UML2 Profile for RDF and OWL to support reuse of UML notation for ontology modeling

The Ontology Definition Metamodel (ODM) specification has been recommended for adoption by the Architecture Board of the OMG (Object Management Group)! (http://www.omg.org/ontology/)

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ODM Metamodel - Standard MOF2 Metamodel

Enable usage of proven OMG software engineering methodologies and tools in ontology-based solution

CL<<metamodel>>

(from org.omg.odm)

TM<<metamodel>>

(from org.omg.odm)

RDFS<<metamodel>>

(from RDF)

RDFWeb<<metamodel>>

(from RDF)

OWLBase<<metamodel>>

(from OWL)

DL<<metamodel>>

(from org.omg.odm)

RDFBase<<metamodel>>

(from RDF)

RDF<<metamodel>>

(from org.omg.odm)

<<merge>>

<<merge>>

OWLDL<<metamodel>>

(from OWL)

OWLFull<<metamodel>>

(from OWL)

<<merge>> <<merge>>

<<merge>> <<merge>>

OWL<<metamodel>>

(from org.omg.odm)

(non-normative)

Package Overview Metamodel Snapshot

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ODM Transformation - UML to OWL Mapping

Enable reuse of enterprise existing models and semantic interoperability

Model Input & Transformation

Semantic Enrichment

OWL Ontology Editor

ER Diagram

UML Class Diagram

Java Interface

DDL

Model Output Transformation

OWL Ontology

OWL

Build OWL Ontology from Existing Models

Mapping Definitions in QVT

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ODM Profile - UML Profile for RDF and OWL

Enable reuse of UML tooling for ontology modeling to support end to end development lifecycle of ontology-based solution

Use Case Diagram(Requirement Gathering)

Sequence Diagram(Requirement Analysis)

Ontology Diagram(Ontology Modeling)

Class Diagram(Object Modeling)

Package Diagram(Implementation)

Solution User

…

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ODM Implementation - IODT

Integrated Ontology Development Toolkit (IODT) Implements Ontology Definition Metamodel

ODM Metamodel(Fully Implemented)

ODM Mapping(Partially Implemented)

ODM Profile(Partially Implemented)

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Selected Application – HyperModel

Semantic Classification

Message or Component Discovery and Reuse

Unify XML Naming and Design Rules

Semantic Validation of Messages

Mapping Between Message Vocabularies

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Where’s IBM China Research Lab

Semantic Information Retrieval

Semantic Web EnabledSoftware Engineering

Semantic InformationManagement

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What semantic web applications you want to develop?

Inputs from SJTU students:- He xiao bin, semantic OS- Zhou qi, semantic file system- Chen long de, semantic question & answering system

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Sample Application Scenarios – XYZ 2.0

Distributed Semantic Desktop- How to manage semantic desktop in a collaborative environment to enable better per

sonal information sharing (P2P 2.0?)

Semantic Software Development- How to ease software design and development by encouraging collaborative develop

ment and knowledge reuse (MDA 2.0?)

Semantic Blog- How to easily publish semantic articles in your blog by integrating your articles in BB

S, email, chat logs and papers etc. that you want to publish (Blog 2.0?) Database and Semantic Web

- How to quickly publish structured data in relational database or XML data as semantic data (Database 2.0?)

Semantic Web Services- How to enable flexible and active service binding and mediation (SOA 2.0?)

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References & Acknowledgement

References- Unicorn Solution Whitepaper, Semantic Information Management- Network Inference Whitepaper, Enterprise Semantic Web- SWAD-Europe Deliverable 12.1.1: Semantic web applications - analysis and selection- Semantic Wikipedia, WWW2006- All ISWC2006 papers in this presentation- 何克清 , 软件服务生态中的非确定性科学问题、互操作性的应用基础问题- MDA Guide Version 1.0.1

Acknowledgement- Lei Zhang contributed several slides about semantic information retrieval- Rama Akkiraju contributed several slides about creole- This presentation used several slides from Yue Pan, and some of them might be from the followi

ng people: Tim Berners-Lee, W3C Ivan Herman, W3C Steve Bratt Grigoris Antoniou Frank van Harmelen

- Developers of those cool applications that are mentioned in this presentation

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Q&A

Thanks

Documents

IBM © Copyright IBM Corporation 2006 Guo Tong Xie ( ) [email protected] Semantic Integration, IBM China Research Lab Semantic Web Applications ABC