the semantic web, applications and migration path at hp laboratories

The Semantic Web, Applications and Migration Path

at HP Laboratories

Bernard BurgManager, Associative Metadata Department, HP Labs Palo [email protected]

7 August, 2003 RMIT Melbourne

/7/2003 RMIT Melbourne, Semantic Web & HP

HP Fast Facts

• Company name: Hewlett-Packard Company

• Headquarters: Palo Alto, California

• CEO and Chairman: Carleton S. (Carly) Fiorina

• HP serves more than one billion customers in more than 160 countries on five continents

•141, 000 Employees Worldwide•$72B company


HP’s Mission

•HP's mission is to invent technologies and services that drive business value, create social benefit and improve the lives of customers—with a focus on affecting the greatest number of people possible.

•HP dedicates $4 billion (U.S.) annually to its research and development of products, solutions and new technologies.


HP is

#1 globally in personal computers

#1 globally in imaging and printing

#1 globally in enterprise storage

#1 globally in management software

#1 globally in UNIX, Windows and Linux servers

#3 globally in IT services


HP’s 4 Global Business Units

Personal System Group

Enterprise Systems Groups

Imagingand

Printing GroupPrinting and

multifunction

Digital Photograph

yScanners

and projectorsSupplies

and accessories

ServersStorage

NetworkingUtility Data

CentersAdaptive

Enterprise

Desktops and

workstations

Notebooks and Tablet

PCSHandheld Devices

HP Services

Software Services


HP Labs’ roles

•Contribute to HP strategy creation and alignment•Deliver technology that enables HP to win in HP’s selected strategies through:

– Breakthrough technologies– Technology advancements

•Create new opportunities for HP that go beyond current strategies

• Invest in fundamental science and technology in areas of interest to HP


HP Labs Worldwide

• Director & SVP Dick Lampman• ~750 employees worldwide• ~5% of $4B HP R&D budget

bristol

japanisraelpalo alto cambridge

india


HP Labs Major Research Areas

Solutions andServices

Internet ComputingPlatform

Printing, Imaging

and Storage

Printing technologies

Imaging Technologies

Digital Photography

Storage (MRAM, ARS)

Utility Data Center

Adaptive Enterprise

Mobile Systems

Trusted Systems

Digital Media Systems

Intelligent Enterprise

TechnologiesSemantic Web

Systems Research

Data Management

Advanced Studies

Quantum Information Processing

Computational Bioscience

Motivation for the Semantic Web

Application Integration

Market and Early Adopters


Interaction Mediation

Shared Model at Interface (Ontology)

Buyer SellerInterface

Interaction

Buyers Model

(Ontology)

Sellers Model (Ontology)

Placed

Shipped

Delivered

Accepted CancelledReturned

Order State

addToBasket

checkOut

Interaction -> effect in terms of state change‘Spontaneous’ state change -> effect in terms of interaction

wilkinso

1) with MPV, list the memories disk product (just release). first, make sure MD encodes as RDF (get an intern to confirm this. :)


Motivating the Semantic Web

from human<->computer interoperability to computer<->computer interoperability

XML, the current web, is not adequate • captures structure, not semantics (relationships, constraints)• tags (properties) have no description• requires humans intermediaries to define mappings

RDF/OWL, the Semantic Web, has promise• RDF models objects, relationships• relationships (properties) are objects (have descriptions)• OWL adds rich constraints• machines can infer mappings (the big hope for interoperability)

The Semantic Web is a W3C standard


The Essence of the Semantic Web

• Semantic modeling is key technology, because it allows machine processing of metadata descriptions

• XML lacks modeling powerApplication integration todayRosettaNetAppli x Appli yMsg 1 Msg 1Msg 2 Msg 2… …Msg k Msg n

Manual mapping

- Brittle – must be updated as msgs evolveMaps elements, not relationships

wilkinso

1) when printed, the "Application integration" line was garbled. Also, RosettaNet appears above "Appli x" and there are two images of the woman and one of a man. i think something is not properly hidden.2) this slide is a little confusing. i think you really want msg 1-n going through the transformation program and the input to the SW compiler should be the Application Msg Schema. Also, the SW Compiler should be renamed ... maybe "Integraton Compiler (SW-based)"3) might add another bullet below the first: "XML lacks modeling power" and, in the talk, emphasize that RDF provides modeling and data interchange while XML provide data interchange only.


Added Value of Semantic Modeling

Application integration with Semantic WebAppli x Appli yMsg schema Msg schema

ontologies

SW Compiler Decrease:- manual mapping - integration timeTransformati

onProgram

aggregation

Increase: - flexibility- resilienceLeverage Semantic Modeling

Msg 1 Msg 1Msg 2 Msg 2… …Msg k Msg nMsg l

wilkinso

1) when printed, the "Application integration" line was garbled. Also, RosettaNet appears above "Appli x" and there are two images of the woman and one of a man. i think something is not properly hidden.2) this slide is a little confusing. i think you really want msg 1-n going through the transformation program and the input to the SW compiler should be the Application Msg Schema. Also, the SW Compiler should be renamed ... maybe "Integraton Compiler (SW-based)"3) might add another bullet below the first: "XML lacks modeling power" and, in the talk, emphasize that RDF provides modeling and data interchange while XML provide data interchange only.


Potential Markets & Early adopters

• Existing market: – Application Integration Software Market

• $4.28B in 2001 $15.53B in 2006 (IDC #27236, June 02)

• New spaces (for HP)– Adaptive Enterprise – The path to semi-structured data mgmt

• SIMILE (HP, MIT, W3C) and Digital Publishing

• Early adopters: – Adobe, Boeing, HP, IBM, SUN Microsystems, …

wilkinso


From the Semantic Web Standard to

a Migration Path


What is the Semantic Web about?

• A pervasive information infrastructure• A web for machines as well as people –

automation, integration, reuse of data across applications

• Web =>• Decentralized• Global scale• Open • Evolvable• Universal representation

wilkinso



What’s the Technology Angle?Why not just XML?

Unicode URIXML + NS + xmlschema

RDF + rdfschemaOntology Vocabulary

Logic

ProofTrust

Digi

tal S

igna

ture

Self-desc. doc.

Data

Data

Rules

• Goal is semantic interoperability• XML gives data exchange

standard for consenting partiesHard to reuse, hard to extend schema, hard to merge data

• RDF gives common data model -> syntactic interoperation

• URIs gives common space of identifiers

• Ontology layer gives explicit conceptual model behind the terms – allows translation between schemas, data integration, reuse, full interoperation

• Logic/proof layer allows exchange of evidence chains (“believe this because …”)

wilkinso



Semantic Web Technologies

• composable, extensible fact/metadata representationgives syntactic interoperability

• RDF triple-model• representation for structure and nature of terms –

ontologiesalso composable and extensibleprovides foundation for semantic interoperability

• description logics• OIL, DAML, DAML+OIL, OWL (lite, DL, full)

• techniques for translating between ontologies, ontology-based data integration

• proof and trust layers for exchange of evidence chains (believe because …)

wilkinso



RDF in a nutshell

• A data model for assertions about things labelled by URIs plus an XML syntax

• all facts are “subject -> predicate -> object” triplesthese form a graph of assertions

• predicates disambiguated by XML namespace• everything is a resource (or a literal string)• can “reify” assertions so can assert

“W3C claims ‘RDF importance veryHigh’”

http://doc

Joe SmithIllustrator

dc:creator

rdf:valuedcq:creatorType

wilkinso



Ontology in a nutshell

• a formal, explicit specification of a shared conceptual model (aka domain model)

• describes the terms used and their relationships • concept names and concept hierarchy• roles (predicates) and role hierarchy• concept expressions, associated axioms

• could think of it as a glorified schemaentity-relationship models are a subset

wilkinso



What HP does for you!

Nuin: agent toolkit

Joseki: RDF Canonicalisation

Source of picture: W3C

Jena 1

2002 Jena1 is used by more than 60% of the community2003 Jena2 is still the leader

Jena2


Progress on Technology – From Jena 1 to Jena 2

The RDF API

ARP

RDF Filter

n-triples

Readers

XML

XML

n-triples

Writers

Mem RDB BDBStores

The DAML API

RDQL

Applications

Jena 1 ArchitectureJena 2 = Jena 1 plus• Full support for RDF2003

The RDF 2003 API

• Generalised ontology API with profiles for the OWLs, DAML+OIL, RDFS,…

Ontology API

OWL Full

OWL DL

OWL Lite

DAML+OIL

RDFS

• Event handling

Rule Systems

RDQL

Applications

• Rule Systems• OWL Syntax Checker OWL

• Extensible reasoning support for RDFS and OWL Lite, including support for external plug-in reasoners

RDFS OWL Lite

External reasoners

• Fast-path database query (via Genesis)

Fast path query

• Efficient reification

• Necessitated complete rearchitecture

Reification Event handling

The RDF 2003 API

Jena SPI

Jena 2 Architecture


JosekiCoarse-grained RDF processing• A NetAPI

– standard operations on models– coarse-grain wrapper to local fine-grained

interaction• Application framework for RDF applications

– Application paradigm• Publishing RDF data

– Large RDF models• Multiple applications collaborating

– Shared, updated RDF


The Nuin agent engine

• A BDI agent engine, written in Java– based on Rao’s AgentSpeak(L) languge [Rao 1997]– extensible knowledge representation based on FOPC with

actions

• designed to be programmer extensible at all points

• default capabilities to make it easy to write agent behaviour “out-of-the-box”– interpreter for abstract actions – built-in action library of core capabilities– script parser for human-readable script syntax– abstract services to allow pluggable connection to

infrastructure service providers (FIPA platforms, SOAP, Joseki, etc)

– integrated with Jena for semantic web processing


Nuin architecture overview

agent core

reasonerreasonerreasoner

knowledge source

interpreter

knowledge source’

beliefsdesires

intentions

plan library

abstract service adapter layer

message service directory service Java objectinvocation

JADE agent platform

event andmessage queue

evaluationfunctions

action library

agent configuratio

n (rdf)

RSS translatorexample concrete services

serialized agent

script(s)


Genesis: migration path of SW

OptimizationSemi-autonomous

performance analysis,

benchmark, tuning,STOR

Apps (EAI/SIMILE)

Genesis

Jena 2

Database

Ease of UseHigher-level objects

ImmutabilitySecurity

Distribution/Caching

ScalabilitySupport Jena 2 API

App-specific schemasMySQL,

PostgreSQL,Oracle

Efficient Graph Queries

Distributed Genesis models on top of scalable, persistent Jena

wilkinso

1) typo: "efficient"2) rather than "first implementation of genesis" say something like "dsitributed genesis models on top of scalable, persistent Jena"3) maybe retitle this slide as "significant result in last 6 months - infrastructure"


How to use these tools

• Currently Available

– Jena 2, Joseki– Open source, BSD license, no restrictions to use– http://www.hpl.hp.com/semweb/index.html

• Announced for October– Nuin– Open source, BSD license, no restrictions to use– http://www.hpl.hp.com/semweb/index.html

wilkinso


Mobile Users, Contexts,

Agents


•are mobile (small devices)

•want immediate solutions to their problems

•have little time to waste

web browsing shows its limits in this context

Our customers


Topology of Mobile Applications

food

@home

Work policiesme

@HPL-PA

hypothesis

•open world: any service, any object, real/virtual

micro-worlds mapped to

•domains (inside firewalls, security, trust, games, work)

•cells (location awareness, cellular nets)

•Need of policies and contexts•Need of semantic descriptions

•Need of proactive behaviour


Building Blocs: Standards

– W3C Semantic Web (ongoing effort)

– FIPA Agents solved the communication problem between Agents (about 20 implementations, 7 open-source)

– Agents are ubiquitous, from server, to laptop, PDA and phone.


Building Blocs: Large Scale Deployment

ParisDublin

Ipswich

LondonChamberyLisbon

BarcelonaParma

SaarbrueckenBerlin

Lausanne Sendai

San Francisco

Sydney

Melbourne Dunedin

Palo AltoSalt Lake City

Honolulu

Miami

Open testbed

70 platforms deployed over 5 continents,

Agentcities Workshop at AAMAS

Web Services, work in Technical committee with:

IBM, HP, Intel, Fujitsu, SAP, Sun Microsystems, Mitre, Motorola…


did we bring the solutions to their problems?

less browsingmore active & pertinent services

due to:superior context awarenessagents proactivity

Added value to our customers

Next Steps


HP as a research partner

– HP is supporting several collaborations in Australia (7?)

– I am working on projects around mobility and context•Monash U. Melbourne (2 projects)•Flinders U. Adelaide•Sydney U.


HP - Australia in General

– HP has high profile collaborations in USA: • MIT, Berkeley (Citrus project) …

– HP has high profile collaborations in EU: • HPL Bristol has European projects, Universities,

student exchange…– HP has high profile collaborations in India:

• HPL India has build an amazing network of connections

• In Australia, we should become the lighthouse project for Semantic Web in context modelling to become HP’s champions


Raising HP’s investments in Australia is

– Build a HP’s network of influence in Australia• Excellence in academia

– Champions in “relevant” domains– Succeed in existing project– Establish student exchange

• Link with industrial tissue– Shared projects with: HP, Academia and industrial

partners– Develop market specific relations

– Increase HP’s revenues Australia

the semantic web, applications and migration path at hp laboratories

Documents

semantic web hpmotivation

semantic web hpwilkinso

rmit melbourne rmit

current web

services rmit melbourne

hprmit melbourne

b companyrmit melbourne

hp labs palo