egc2005 european grid conference,amsterdam, 14-16 feb 2005 (semantic grid) services + semantic (grid...

EGC2005 European Grid Conference,Amsterdam, 14-16 Feb 2005

(Semantic Grid) Services + Semantic (Grid Services)

Professor Carole Goble The University of Manchester, UK

e-Science North West Regional CentremyGrid, OntoGrid, Knowledge Web

GGF Semantic Grid Research Group

EGC2005 European Grid Conference, Amsterdam, 14-16 Feb 2005

“The ongoing convergence between Grids, Web Services and the Semantic Web is a fundamental step towards the realisation of a common service-oriented architecture empowering people to create, provide, access and use a variety of intelligent services, anywhere, anytime, in a secure, cost-effective and trustworthy way.”

Next Generation Grids 2

Requirements and Options for

European Grids Research 2005-2010 and Beyond

EU Expert Group Report July 2004


“To realise the Next Generation Grid requires semantically rich information representation, the exploitation of knowledge, and co-ordination and orchestration that is aware of context and task”

David Snelling, NextGRID

Building Intelligent Grid Services


Knowledge everywhere already…its called metadata

• State properties of a resource– Data in a purchase order– Current usage agreement for resources on a grid– Metrics associated with work load or performance on a Web server

• Declarative descriptions of data sets, codes, services, workflows– Typing and classifying service or workflow inputs, outputs, goals, …

– Access rights to resources

• Declarative descriptions for, and records of, service interactions– event notification topics, provenance trails, monitoring records

• Policy and profile encoding– personal profiles and security groupings

• Used in – job control; workflow composition, semantic dataset integration, resource brokering,

resource scheduling, problem solving selection, intelligent portals…

• GGF WG-CMM, CIM, GIS, MDS, ….


Knowledge and the knowledge producing & consuming protocols & patterns are already in Grid

Middleware and Grid Applications.

Embedded in middleware code, in schemas, in catalogues, in applications and in practice.


Bringing knowledge into the light

Managing and operating a Grid intelligently requires:1. Knowledge

– Knowledge about the state and properties of Grid components, and their configurations

– Mechanisms for interpreting that knowledge

2. Intelligently acquiring and refreshing knowledge

3. Use it practically in decision making.


Convergence

• Semantic Web Technologies

• Semantic Web itself

Grid services

Sem

antic

Web

Ser

vice

s

Semantics for the Grid

Grid services for Semantic Web

Plum

bers

DevelopersWeb

Services

Grid Semantic

Weband Agents

Semantic Grid

Engineers

Aes

thet

ics

Theoreticians


Semantic Web mechanisms

MetadataAnnotationRDF

OntologiesOWL/RDFS

WebXML, URI, UniCode

Deep webPHP, WS*

RulesSWRL

p -> a; p=a

p -> a; p=a

p -> a; p=a

p -> a; p=a

p -> a; p=a

Trust

Search engines and filters

Applications

• Uniform naming scheme.

• Metadata – descriptions of properties and content

• Metadata – glue linking resources together

• Ontologies – interpretation of metadata for people and processes.


Making Knowledge Explicit

OWL Web Ontology Language

RDF Resource Description Framework


Make knowledge explicit.

Make knowledge protocols explicit.

Describe some of these declaratively so they might be exchanged and machine processed.

Metadata data – here is what it is and/or how it relates to something else

Ontologies / controlled vocabularies – we understand each other

OntologyMetadataassertion

Object


Knowledge Stakeholders

Com

puter

ScientistsScientific

Applications

Grid Middleware

Grid platform

and resources

Security policies

standards

Scientists

Ser

vice

Providers

Knowledge for Grid Applications

Knowledge for the operation of the Grid

Sources of Knowledge


Upper domain generic services

Web Service Resource FrameworkWeb Service-Notification

WS-I+

Web Services

Grid Domain Applications

Collective services

Base services

System services“P

lum

bin

g”

Operational Knowledge

Application Knowledge

knowledge worker'sapplications and tools


The Semantic Grid is an extension of the current Grid in which information and services are given well-defined and explicitly represented meaning, better enabling computers and people to work in cooperation

Semantics in and on the Grid

EGC2005 European Grid Conference,Amsterdam, 14-16 Feb 2005

Time to move beyond slogans.


Semantic Grid roadmap

• Exploit the languages from the Semantic Web and other.• Specifying and developing the architectural components and

tools forming the infrastructure of the Semantic Grid and define the architecture of the (Semantic) Grid.

• Prototyping applications using the languages, the components and defining the content necessary.

Developing in parallel, yet are interdependent. A maelstrom of research coupled concurrently with standards

activity, and early experiments and prototypes running alongside (some) commercial developments.


CombeChem

Semantic Grid trajectory

Time

Efforts

Implicit Semantics1st generation

SRB

Implicit SemanticsOGSA generation

GGF Semantic Grid Research Group

Many workshops

Systematic Investigation Phase

Specific experimentsPart of the Architecture

Dagstuhl Schloss Seminar

Grid Resource Ontology

Many projects

Pioneering PhaseAd-hoc experiments, early

pioneers

SDK

Demonstration Phase


Knowledge Aware Grid Services

KAGS


KAGS

Grid CompliantKnowledge Services

GCKS


GCKS

Grid Aware Knowledge Services

GAKS


GAKS

Three strands

(Semantic Grid) Services

Semantic (Grid Services)

And how all these services play togetherProfiles, Protocols, Patterns, Policies

P4P4


Middleware

Functionality: Existing operations for interaction with a knowledge serviceMetadata: How fast? What language is supported?Lifetime Management: Factory methods, creation of resources

Knowledge: Additional port types relating to knowledge, for example discovery.

Use of Grid infrastructure within the implementation of the service.

Three strandsKnowledge Aware

Grid ServicesKAGS


KAGS


GCKS


GCKS


GAKS


GAKS


Grid Compliant Knowledge Services

• Take today’s knowledge services from the Semantic web and other worlds

• What does it mean for them to be Grid Services?

• What are the state properties of an ontology grid service?

• What are the lifetime management properties of an ontology grid service?

• What is a virtualised and dynamically provisioned ontology service, (metadata store, metadata annotator, reasoner …) ?

• How will an ontology grid service and a metadata grid service play together?


Grid Compliant OntologiesResource • A distinguishable unique identity and lifetime (usually static)• Maintains a specific state that can be materialized • May be accessed through one or more Web Services• Artifact - a file, XML document, database, usually real (could be virtual).

Could be compound.

Service• Base interface for inspecting and manipulating an ontology• A well defined “Ask-Tell” API: getSubConcepts(concept),

getSuperConcepts(concept), classify, checkSatisfiability(concept), put(conceptExpression) …

• Resource – a connection to the Ontology Service

• An ontology might be just a file. Or an application. Or embedded in an application after a community has thought about it for a bit.


Ontology as an OGSA-DAI Realization

WS-DAIMessage Patterns

Behavioural Properties

WS-DAIOOntology

WS-DAIXXML

WS-DAIRRelational

WS-DAIO-RDFRDF Specific

WS-DAIO-OWLOWL specific

Provide a realization of WS-DAI with specific ontology messages (activities)


RDF Annotation store as an OGSA-DAI Realization

WS-DAIMessage Patterns

Behavioural Properties

WS-RDF WS-DAIXXML

WS-DAIRRelational

Jena Sesame

DB2 mySQL

Provide a realization of WS-DAI for RDF


Data -> Ontology Access• Data Access collects together messages that access

and/or modify a resource

• Note: the messages are ignorant of the query other than its class.

• OSGA-DIAO

–The message patterns & the behavioural properties

–The API for the ontology querying

–The realisation mapping to the ontology language – OWL, RDF, RDFS, DAG



• Take a Grid service and see how it might take advantage of a knowledge service or knowledge resource.

• Might be a base Grid service or an Application Service or a high level Grid service.

• What are the generic and specific knowledge services required for Grid?

• Two starting points: – Discovery. Registry/Brokering – shared semantics;

resource annotation; painless knowledge recovery.– Debugging – shared semantics; knowledge collection;

knowledge recovery.


• Semantic Web – describing data• Semantic Web Services – describing processes.

– WSMO, OWL-S

Web Service

API

Web Interface

Web Service

API

Generic Schema for Web (Grid) Services

SpecificApplicationOntology

Semantic Web Services

Thierry’s observations about Web Service abstractions


Discovery in Taverna workflow workbench

• Taverna currently ships with access to >1000 publicly available bioinformatics services

• Bioinformatican chooses services when forming workflows, with assistance.

• A common ontology is used to annotate and query any myGrid object including services.

• Discover workflows and services described in the registry via Taverna.

• Look for all workflows that accept an input of semantic type “nucleotide sequence”


Low level descriptions

WSDL, Scufl

Feta importer

UDDI registry

myGrid domain classification

Reasoner

PeDRo annotator

Feta semantic discovery

engine

Feta GUI

Taverna workbenchclients

KAVE provenance

Ontology editor

Annotator

Resourcematch make

Knowledge Engineer

Ontologist builds myGrid Domain Ontology

Feta skeletons generated by mining low level descriptions

Skeletal descriptions are annotated

Descriptions are loaded and engine initiated

Search requests

User interacts with GUI to discover resources

Semantic Discovery

Annotated descriptions are stored

Metadata discoveryOntology Acquisition

Resource discovery


Intelligent Debugging Architecture

Acklin


19747251 AC005089.3831Homo sapiens BAC

clone CTA-315H11 from 7, complete sequence15145617 AC073846.6

815Homo sapiens BAC

clone RP11-622P13 from 7, complete sequence15384807 AL365366.20

46.1Human DNA sequence

from clone RP11-553N16 on chromosome 1, complete sequence7717376 AL163282.2

44.1Homo sapiens

chromosome 21 segment HS21C08216304790 AL133523.5

44.1Human chromosome 14

DNA sequence BAC R-775G15 of library RPCI-11 from chromosome 14 of Homo sapiens (Human), complete sequence34367431 BX648272.1

44.1Homo sapiens mRNA;

cDNA DKFZp686G08119 (from clone DKFZp686G08119)5629923 AC007298.17

44.1Homo sapiens 12q22

BAC RPCI11-256L6 (Roswell Park Cancer Institute Human BAC Library) complete sequence34533695 AK126986.1

44.1Homo sapiens cDNA

FLJ45040 fis, clone BRAWH302048620377057 AC069363.10

44.1Homo sapiens

chromosome 17, clone RP11-104J23, complete sequence4191263 AL031674.1


from clone RP4-715N11 on chromosome 20q13.1-13.2 Contains two putative novel genes, ESTs, STSs and GSSs, complete sequence17977487 AC093690.5

44.1Homo sapiens BAC

clone RP11-731I19 from 2, complete sequence17048246 AC012568.7

44.1Homo sapiens

chromosome 15, clone RP11-342M21, complete sequence14485328 AL355339.7


from clone RP11-461K13 on chromosome 10, complete sequence5757554 AC007074.2

44.1Homo sapiens PAC

clone RP3-368G6 from X, complete sequence4176355 AC005509.1

44.1Homo sapiens

chromosome 4 clone B200N5 map 4q25, complete sequence2829108 AF042090.1

44.1Homo sapiens

chromosome 21q22.3 PAC 171F15, complete sequence

>gi|19747251|gb|AC005089.3| Homo sapiens BAC clone CTA-315H11 from 7, complete sequenceAAGCTTTTCTGGCACTGTTTCCTTCTTCCTGATAACCAGAGAAGGAAAAGATCTCCATTTTACAGATGAGGAAACAGGCTCAGAGAGGTCAAGGCTCTGGCTCAAGGTCACACAGCCTGGGAACGGCAAAGCTGATATTCAAACCCAAGCATCTTGGCTCCAAAGCCCTGGTTTCTGTTCCCACTACTGTCAGTGACCTTGGCAAGCCCTGTCCTCCTCCGGGCTTCACTCTGCACACCTGTAACCTGGGGTTAAATGGGCTCACCTGGACTGTTGAGCG

urn:lsid:taverna:datathing:15

..BLAST_Report

rdf:type

urn:lsid:taverna:datathing:13

..similar_sequences_to

.. nucleotide_sequence

rdf:type

service invocation

..created_by

workflow invocation

workflow definition

experiment definition

project

person

group

service description

organisation

..described_by

..run_during

..invocation_of

..part_of

..works_for

..part_of

..part_of

..author

..author

..run_for

A B

..masked_sequence_of

..filtered_version_of

Relationship BLAST report has with other

Other classes of information related to BLAST report

Keeping track

Jun Zhao, Chris Wroe, Carole Goble, Robert Stevens, Dennis Quan, Mark Greenwood, Using Semantic Web Technologies for Representing e-Science Provenance in Proc 3rd International Semantic Web Conference, Hiroshima, Japan, Nov 2004



• What is the architecture of distributed knowledge services?• Can Grid platforms realistically provide a robust distributed

stateful computing platform for agent systems?• OGSA-DAIS for RDF repositories.• Replica location service for replicated knowledge services.• Secure file transfer for metadata.• Event notification for metadata or ontology updates.• Authentication and authorisation for updates.• Metadata updated by workflows; • Security and RDF! • Distributed reasoning !!

• Depends on the availability of these Grid services.


WS-Notification and Semantic Integrity

• Subscriber – an Annotation Service - indicates interest in a particular (semantic) topic – Ontology Version change - by issuing a subscribe request

• Subscriptions are WS-Resources– Various subscriptions are possible

• Notification may be triggered by:– WS Resource Property value changes– Other “situations”

• Broker examines current subscriptions • Brokers may

– “Transform” or “interpret” topics <- knowledge!

Broker

Subscriber

Publisher

subscribe

subscribe

S S S

notify

notify

notify

notify

Metadata service

Ontology Service

Adapted from Dr. Daniel Sabbah, IBM, Globus World 2004.


resource discovery, intelligent debugging, provenance mining

Car repair settlement, satellite data configuration.

Grid Application and Application Services

OGSAplumbing services

OGSA OntoKit

semantic grid services

OGSA OntoKit

knowledge Generation services

Base services: annotation managementontology access and integration, annotation access, reasoning, ontology alignment GRID PROPERTIES

Resources Resources: Ontology, Knowledge Base, Registry, Database DOMAIN & MIDDLEWARE

OGSA OntoKitplumbing services

Patterns & Upper Services: Semantic broker, semantic registry, semantic logging, semantic workflow management, vocabulary management PATTERNS OF INTERACTION

Yet Another Stack


Obstacles to Overcome• Semantic what?• Compelling use cases

– “Revolution is only possible when it becomes inevitable”– Niche activity.

• No content or hard to get the content!– Ontology acquisition. Pain-free metadata acquisition.

• Baggage of communities– Different agendas– Hendler Principle: “A little semantics goes a long way”.– Failure to mainstream – agents

• Instability of both platforms– Middleware hard to use and incomplete– Off putting to “the other side”– Deployment, research, development, applications and standardisation all happening

together

• Whither Grid Architecture?


MDA and the Grid• Where is grid?

– current grids are on a platform level

– grids compatible with service oriented architectures are on ASM level

• Challenge:– should grids do better than

SOA based on Web Services?– automatic transformation of

PIM models into a grid specific ASMs and PSMs

• Opportunity:– transform a business level

architectures to Web Services, Grid, whatever-comes-next platform

Computation Independent

Model

PlatformIndependent Model

ArchitectureSpecific Model

Platform Specific Model

working system

e.g. OGSA

e.g. GT4, gLite

manual

automatic

automatic

semi automatic

Prof.dr. Žiga Turk


Map concepts between ontologies

• Unicore and GLUE have different philosophies for describing resources :-(• In Unicore, the resources are described in terms of resource requests • In GLUE, resources are described in terms of the availability of resources.


Use

AssertionImplicit

Implicit

Explicit

Explicit

Shared human consensus

Text descriptions

Type systems Schemata

OntologiesRulesNon-embedded metadataEmbedded metadata

Not all knowledge will use separate services


Source of metadata and knowledge

• Grid Resource Ontology• Activation Energy• Metadata mining• The network effect – service providers rule• Return on investment for service providers and users• Applications keep it real: listen to users to take short cuts.


Semantic proportionsspeculation – no empirical foundation at all

Resource

Generic Grid

Application


• Knowledge aware grid servicesGrid Knowledge,

Agents & the Semantic Web

Overcoming community divisionsGrowing pains of middleware

Make it easier not harder or more “interesting”A little semantics goes a long way

Evolution not revolution Technology push

http://www.gridforum.org/


“WSRF is the instruction set of the Grid” Thierry Priol

WSRF WS-I+

Grid service behaviour

Semantic Grid Services


Whither Grid Architecture?


ApplicationsUse Cases

Semantic GridArchitecture

GridArchitecture

SemanticArchitecture

InteliGrids

ProvenanceSIMDAT

NextGRID

WSRF

UniGrids

WS-I+

K-WfGrid

SDK


Summary

• What existing technologies can we harness and what needs to be done that is new?

• Semantic SOA – what are the resources, services, profiles, patterns and policies?

• What are the appropriate abstractions for a Semantic Grid based architecture? (or a Grid Architecture?)

• How will semantics make the Grid more flexible and simpler – and how do we avoid making it more complicated!

• How do we ensure close cooperation with design and development of next generation Grid research and next generation knowledge research?


Thanks• myGrid consortium, esp. Phil Lord, Pinar Alper, Chris Wroe,

Luc Moreau• OntoGrid project members• Norman Paton, OGSA-DAI• Prof.dr. Žiga Turk, InteliGrids• John Brooke, UniGrids• Stephane Viali• Thierry Pioli, CoreGrid• David de Roure, GGF Sem-Grd RG

http://www.semanticgrid.org/

egc2005 european grid conference,amsterdam, 14-16 feb 2005 (semantic grid) services + semantic (grid...

Documents

grid grid services

grid applications

grid middleware

grid metrics

knowledge knowledge

properties of grid components

exploitation of knowledge

refreshing knowledge