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Business Semantic Web

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Information about Business Semantic Web

Published on January 1, 2008

Author: erant

Source: slideshare.net

Description

A lecture I gave given in a seminar at the MBA school of the Hebrew University, Israel
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Is The Semantic Web Ready for Business? Eran Toch May 2005 Information Systems Engineering Area Faculty of Industrial Engineering and Management Technion – Israel Institute of Technology

Agenda Why do we need it? What is it? Challenges and Opportunities Applications Current Commercial Activities Semantic Web Services Social Software Summary

Why do we need it?

What is it?

Challenges and Opportunities

Applications

Current Commercial Activities

Semantic Web Services

Social Software

Summary

The WWW Technically A set of protocols and languages driven by a strong standards approach: URI HTTP HTML XML Principles: Implementation and platform independence crucial World Wide Web Consortium the most prominent

A set of protocols and languages driven by a strong standards approach:

URI

HTTP

HTML

XML

Principles:

Implementation and platform independence crucial

World Wide Web Consortium the most prominent

Problems with the WWW 65,900,000 results were returned Google - Market Cap:72.45 B $

65,900,000 results were returned

Google - Market Cap:72.45 B $

More Problems: Comparison Shopping Shopping.com - Market Cap : 502.70 M $

Shopping.com - Market Cap : 502.70 M $

Building Shopping Comparison Engine

Trust Spam Phishing E-Commerce Who can you trust to send you emails? Is this site is the one it claims to be? How can I know for sure if a transaction really occurred?

Problem Domains The General Web Data-mining activities (e.g. search, comparison, notification) Transactions (e-comm, e-gov) Business Knowledge bases Intranets, data warehouses Collaborative Computing Transaction between systems Knowledge-based businesses biology, law etc

The General Web

Data-mining activities (e.g. search, comparison, notification)

Transactions (e-comm, e-gov)

Business Knowledge bases

Intranets, data warehouses

Collaborative Computing

Transaction between systems

Knowledge-based businesses

biology, law etc

Agenda Why do we need it? What is it? Challenges and Opportunities Applications Current Commercial Activities Business Models Social Software Semantic Web Services Summary

Why do we need it?

What is it?

Challenges and Opportunities

Applications

Current Commercial Activities

Business Models

Social Software

Semantic Web Services

Summary

The Semantic Web [SciAme] “ The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.” Sir Tim Berners-Lee

Making the Web Machine-Friendly Making knowledge self explainable for machines Creating an environment for knowledge inference Establishing trust

Making knowledge self explainable for machines

Creating an environment for knowledge inference

Establishing trust

Making it Meaningful for Machines WWW Resource Humans Machines <RDF> http://www.amazon.com/4344533

Knowledge For Machines P roduct $14.99 Soundrack Audio CD Universal 24 hours Kissing Jessica Stein hasPrice hasTitle availability itsLabel itsType is a http://www.amazon.com/4344533 RDF – Resource Description Framework [REF]

Ontologies An ontology is standard for some knowledge domain, e.g. Healthcare Bioinformatics CRM Web services It provides a formal and agreed upon controlled vocabulary, which is used to define concepts Information can be tagged according to these concepts Healthcare Disease Medicine Product Price Doctor Patient Is a treats takes Is treated by has prescribe

An ontology is standard for some knowledge domain, e.g.

Healthcare

Bioinformatics

CRM

Web services

It provides a formal and agreed upon controlled vocabulary, which is used to define concepts

Information can be tagged according to these concepts

Web Ontology Language (OWL) OWL is an RDF-based language for Ontology modeling. Enable class and instance definition, using relations and properties such as: Properties (price is a property of product) subClassOf (Employee is subClassOf Person) intersectionOf (music CD is intersectionOf playable thing and consumer product) Cardinality constrains (product has 1 (and only 1) price properties) OWL ontologies can be developed independently, having concepts reference each other

OWL is an RDF-based language for Ontology modeling.

Enable class and instance definition, using relations and properties such as:

Properties (price is a property of product)

subClassOf (Employee is subClassOf Person)

intersectionOf (music CD is intersectionOf playable thing and consumer product)

Cardinality constrains (product has 1 (and only 1) price properties)

OWL ontologies can be developed independently, having concepts reference each other

Ontologies E-Commerce Healthcare Disease Medicine Product Price Customer Doctor Supplier RFID Patient Is a Is a treats takes Is treated by supplies has buys has

Generalizing Knowledge Networks P roduct Price Medicine Side Effect OTC Medicine Prescription Is a Is a Is a Price Comparison Robot Hospital Drug Monitor Robot

The Network Effect E-Commerce Site E-Commerce Site E-Commerce Site Library Personal Computer Song Path Product Price Item Catalog ID Is a Is a

Agenda Why do we need it? What is it? Challenges and Opportunities Applications Current Commercial Activities Semantic Web Services Social Software Summary

Why do we need it?

What is it?

Challenges and Opportunities

Applications

Current Commercial Activities

Semantic Web Services

Social Software

Summary

Business on the Semantic Web Business Processes BP Reasoning Storing metadata (databases, messaging) Creating Metadata (editors, translators, automatic extraction, services)

Bottlenecks Sufficient metadata is the main bottleneck of the Semantic Web There is a loop: Without metadata, no applications will be built Without applications, no one will create metadata Academic The Metadata gap Commercial

Sufficient metadata is the main bottleneck of the Semantic Web

There is a loop:

Without metadata, no applications will be built

Without applications, no one will create metadata

Metadata Chasm Ontology creation requires companies and organization to standardize their concepts, much harder than to standardize communication protocols Ontology creation requires large investments. Because ontologies reduce the uncertainty of information, their benefits will be revealed mainly in the long run. Thus, they do not provide immediate return on the investment, not immediately [KIM]. However, in some markets, ontologies may have faster cost-to-benefit cycle.

Ontology creation requires companies and organization to standardize their concepts, much harder than to standardize communication protocols

Ontology creation requires large investments. Because ontologies reduce the uncertainty of information, their benefits will be revealed mainly in the long run.

Thus, they do not provide immediate return on the investment, not immediately [KIM].

However, in some markets, ontologies may have faster cost-to-benefit cycle.

Markets Niece fields on the general WWW Content syndication Communications and social networks Business Processes Handling interoperability Extending Service Oriented Architecture (SOA) Knowledge-rich markets Bioinformatics Software Engineering Law Business Intelligence Business intelligence using semantic annotations

Niece fields on the general WWW

Content syndication

Communications and social networks

Business Processes

Handling interoperability

Extending Service Oriented Architecture (SOA)

Knowledge-rich markets

Bioinformatics

Software Engineering

Law

Business Intelligence

Business intelligence using semantic annotations

Agenda Why do we need it? What is it? Challenges and Opportunities Applications Current Commercial Activities Business Models Social Software Semantic Web Services Summary

Why do we need it?

What is it?

Challenges and Opportunities

Applications

Current Commercial Activities

Business Models

Social Software

Semantic Web Services

Summary

Semantic Web Applications Adobe - uses RDF as a basis for documenting meta-data, in PDF and other tools Boeing – uses RDF and OWL in several internal projects AGFA – uses RDF to categorize medical photos NOKIA – lots of Semantic Web activities. Including RDF knowledge store IBM – Strong research activities

Adobe - uses RDF as a basis for documenting meta-data, in PDF and other tools

Boeing – uses RDF and OWL in several internal projects

AGFA – uses RDF to categorize medical photos

NOKIA – lots of Semantic Web activities. Including RDF knowledge store

IBM – Strong research activities

Aduna Netherlands-based startup Main products: Semantic desktop search Semantic enterprise search Semantic Metadata server [ADUNA]

Netherlands-based startup

Main products:

Semantic desktop search

Semantic enterprise search

Semantic Metadata server

Celcorp Based in Santa-Monica Claim to have 3 customers from Fortune 500 Main business: Semantic EAI (Enterprise Application Integration) Main product: Celware Intelligent Access Records user actions in legacy systems Builds an editable knowledge based of reusable task models Generates executable processes, based on the tasks Business processes are automatically planned and executed, using the knowledge base [CELCORP]

Based in Santa-Monica

Claim to have 3 customers from Fortune 500

Main business: Semantic EAI (Enterprise Application Integration)

Main product: Celware Intelligent Access

Records user actions in legacy systems

Builds an editable knowledge based of reusable task models

Generates executable processes, based on the tasks

Business processes are automatically planned and executed, using the knowledge base

Brandsoft Based in Los Gatos, CA Main product: Brandsoft Resource Manager Content management and application development suite, based on RDF

Based in Los Gatos, CA

Main product: Brandsoft Resource Manager

Content management and application development suite, based on RDF

Cerebra Based in Carlsbad, CA. AKA Network Inference. Claim to have more than 25 customers, some of them from Fortune 500 Cerebra Server – Provides ontology management and storage Semantic integration of data from RDBMS etc Querying through XQuery Cerebra Construct – Ontology modeling using MS-Visio Professional Services [CEREBRA]

Based in Carlsbad, CA. AKA Network Inference.

Claim to have more than 25 customers, some of them from Fortune 500

Cerebra Server –

Provides ontology management and storage

Semantic integration of data from RDBMS etc

Querying through XQuery

Cerebra Construct –

Ontology modeling using MS-Visio

Professional Services

Tucana Based in Reston, VA. Their main product, Tucana Knowledge Discovery Suite, is a semantic knowledge base, with some business intelligence abilities. It is built upon: Scaleable RDF triple store Reasoning engine Metadata extraction from RDBMS, files, emails, ERP etc. [Tucana]

Based in Reston, VA.

Their main product, Tucana Knowledge Discovery Suite, is a semantic knowledge base, with some business intelligence abilities. It is built upon:

Scaleable RDF triple store

Reasoning engine

Metadata extraction from RDBMS, files, emails, ERP etc.

Semantic Web Services 1. The customer’s agent automatically locates and invokes the brokerage firm’s Web service 2. Domain and Service models can be used to automatically or manually compose services

Semantic Web Services, cont’d OWL-S is an upper ontology for a semantic description of Web services. E.g. an input message can be typed as the concept “Product”, and not just a String Describes a Web service by: What it does (inputs, outputs, preconditions…) How it works (a process model) Grounding to an invocation method (WSDL) [OWL-S]

OWL-S is an upper ontology for a semantic description of Web services.

E.g. an input message can be typed as the concept “Product”, and not just a String

Describes a Web service by:

What it does (inputs, outputs, preconditions…)

How it works (a process model)

Grounding to an invocation method (WSDL)

Semantic SOA (Service Oriented Computing) Order product Order Management Employee Signoff Report employee daily activities check order status Update inventory Get customer History Check user security profile Get incoming messages Customer Care

FOAF Stands for &quot;Friend Of A Friend“* Provides a template for metadata about people, and their interests, relationships and activities An open community-lead and open-source initiative [FOAF]

Stands for &quot;Friend Of A Friend“*

Provides a template for metadata about people, and their interests, relationships and activities

An open community-lead and open-source initiative

FOAF Example <Person> Name Website Picture Email <Person> <Person> knows knows

FOAF-Based Applications FOAF Explorer: More Job search Dating Identity Security [http://xml.mfd-consult.dk/foaf/explorer/]

FOAF Explorer:

More

Job search

Dating

Identity

Security

FOAF-Applications – cont’d FOAFNaut - <http://www.foafnaut.org/>

FOAFNaut - <http://www.foafnaut.org/>

Email Trust with FOAF [TRUST]

Inferring Trust me trust trust trust Don’t trust trust trust trust email email Email is blocked Email is accepted

Agenda Why do we need it? What is it? Challenges and Opportunities Applications Current Commercial Activities Business Models Social Software Semantic Web Services Summary

Why do we need it?

What is it?

Challenges and Opportunities

Applications

Current Commercial Activities

Business Models

Social Software

Semantic Web Services

Summary

Summary Widespread Use Academia desert Where would the semantic web go

Key Points for Success Crossing the metadata chasm Automatic extraction of metadata in predefined domains Reducing the turn-on-investment cycle. Making ontologies useful, now Niece markets Bioinformatics Software engineering Business Processes Leveraging semantic markup with Web services and enterprise computing

Crossing the metadata chasm

Automatic extraction of metadata in predefined domains

Reducing the turn-on-investment cycle. Making ontologies useful, now

Niece markets

Bioinformatics

Software engineering

Business Processes

Leveraging semantic markup with Web services and enterprise computing

Long Term Implications of a Success New professions: Ontology editors Taggers Agents Many automated tasks (shopping, travel, dating…) Bigger threats on human agents (travel agents, insurance agents…) Business Processes IT missions change - from constructing applications to providing frameworks Work of operational personnel change – from requirement definitions to business process modeling

New professions:

Ontology editors

Taggers

Agents

Many automated tasks (shopping, travel, dating…)

Bigger threats on human agents (travel agents, insurance agents…)

Business Processes

IT missions change - from constructing applications to providing frameworks

Work of operational personnel change – from requirement definitions to business process modeling

References [SciAme] Berners-Lee, T., Hendler, J., Lassila, O., The Semantic Web , Scientific American, 284(5), 2001, pp. 34-43. [RDF] http://www.w3.org/RDF , http://www.ilrt.bris.ac.uk/discovery/rdf [OWL] http://www.w3.org/TR/owl-guide [KIM] Kim, Henry M. (2002). &quot; Predicting How Ontologies for the Semantic Web Will Evolve &quot;, Communications of the ACM , Vol. 45, No. 2, pp. 48-54. [FOAF] http :// www . foaf - project . org / [ADUNA] http://aduna.biz [CELCORP] http://www.celcorp.com [CEREBRA] http://cerebra.com [OWL-S] http://www.daml.org/services [TRUST] http://trust.mindswap.org

[SciAme] Berners-Lee, T., Hendler, J., Lassila, O., The Semantic Web , Scientific American, 284(5), 2001, pp. 34-43.

[RDF] http://www.w3.org/RDF , http://www.ilrt.bris.ac.uk/discovery/rdf

[OWL] http://www.w3.org/TR/owl-guide

[KIM] Kim, Henry M. (2002). &quot; Predicting How Ontologies for the Semantic Web Will Evolve &quot;, Communications of the ACM , Vol. 45, No. 2, pp. 48-54.

[FOAF] http :// www . foaf - project . org /

[ADUNA] http://aduna.biz

[CELCORP] http://www.celcorp.com

[CEREBRA] http://cerebra.com

[OWL-S] http://www.daml.org/services

[TRUST] http://trust.mindswap.org

Thank You [email_address] http:// www.technion.ac.il/erant

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