Dietze Aswc 2009 Final

Two-Fold Service Matchmaking –Applying Ontology Mapping for Semantic Web Service Discovery

/// ASWC’09, Shanghai, China, December 08, 2009

Stefan Dietze1, Neil Benn1, John Domingue1, Alex Conconi2, Fabio Cattatoni2

1Knowledge Media Institute, The Open University, UK

2TXT eSolutions, Italy

08/12/2009 4th Asian Semantic Web Conference

� Semantic Web Services (SWS) mediation

� Two-fold matchmaking approach for SWS

� Prototypical implementation & application

� Conclusions

Outline


sws:WebServiceSWS.2

sws:WebServiceSWS.3

sws:WebServiceSWS.1

WebServiceWS.2

WebServiceWS.3

WebServiceWS.1

Introduction Semantic Web Services (SWS)

� Formalisations of Web services in

terms of capabilities (Cap),

interfaces (If) and non-functional

properties (Nfp)

� Capabilities: assumptions (Ass) and

effects (Eff)

� Use ontologies O (i.e. tuple of

concepts C, instances I, properties

P, relations R and axioms A)

� Reference models e.g. OWL-S,

WSMO, SAWSDL


� SWS discovery: matchmaking of

capabilities of SWS e.g. :

SWS matchmakingIssues

1212EfEfAsAs ⊂∪⊂

sws:WebServiceSWS.2

sws:WebServiceSWS.3

sws:RequestR.1

sws:WebServiceSWS.1

WebServiceWS.2

WebServiceWS.3

WebServiceWS.1

? ?




� I.e., matching logical expressions


211 IIAs ∩¬≡


sws:WebServiceSWS.2

sws:WebServiceSWS.3

sws:RequestR.1

sws:WebServiceSWS.1

WebServiceWS.2

WebServiceWS.3

WebServiceWS.1

432 IIAs ¬∩≡

has-assumption

has-assumption




� I.e., matching logical expressions…

� …which are heterogeneous.


211 IIAs ∩¬≡


sws:WebServiceSWS.2

sws:WebServiceSWS.3

sws:RequestR.1

sws:WebServiceSWS.1

WebServiceWS.2

WebServiceWS.3

WebServiceWS.1

?

432 IIAs ¬∩≡

<Location rdf:ID="Milton_Keynes"/>

<geospatialLocation rdf:ID="M-K"/>

has-assumption

has-assumption




� I.e., matching logical expressions…

� …which are heterogeneous.

� Requires: mediation between

concepts/instances across

heterogeneous SWS.

SWS matchmakingSemantic-level mediation


sws:WebServiceSWS.2

sws:WebServiceSWS.3

sws:RequestR.1

sws:WebServiceSWS.1

WebServiceWS.2

WebServiceWS.3

WebServiceWS.1

Semantic-Level Mediation

Mediation between heterogeneous

semantic representations


Proposal:

� SWS matchmaking as two-fold process

(i) Semantic mediation via ontology (instance) mapping

(ii) Logical reasoning for matchmaking of capability/interface descriptions

SWS matchmaking Two-fold process


Proposal:

� SWS matchmaking as two-fold process

(i) Semantic mediation via ontology (instance) mapping

(ii) Logical reasoning for matchmaking of capability/interface descriptions

Issues:

� Traditional SWS matchmaking focusses on (ii)

� Integration of (i):

� Via manual mappings? - costly

� Via exploitation of linguistic or structural similarities? - prone to errors

� Representations allowing for implicit similarity-computation ?

SWS matchmaking Two-fold process


� Refining SWS ontologies through multiple “Mediation Spaces” (MS), i.e. multidimensional,

vector spaces

� Through MS ontology (extends SWS descriptions)

� Concept C in SWS ontology O => Mediation Space MS / Instance I of C => member M

(vector) in MS

Semantic-level mediationApproach: instance similarity computation in shared MS

( ){ }ℜ∈∈= iinn

npMSddpdpdpMS ,,...,,

2211

Instance I1j Instance I1i

Concept C1x instance-of

refined-as-ns

refined-as-member refined-as-member

d1

d2

d3

instance-of

SWS Ontology O1

Mediation Space MS1x


� Similarity-computation between SWS instances => spatial distances in MS

� e.g. Euclidean distance:

� Common agreement at schema (i.e. MS) level

∑=

−−

−=

n

i v

i

u

ii

s

vv

s

uupvudist

1

2))()((),(

Semantic-level mediationApproach: instance similarity computation in shared MS

d2

Instance i2i Instance i1i

Mediation Space MSx

Concept c1x

instance-of refined-as-ms

refined-as-member refined-as-member

Concept c2x

refined-as-ms

d1

d3

SWS Ontology O1 SWS Ontology O2

instance-of

Agent 1 Agent 2


wsmo:Mediator

Med.1

wsmo:WebService

SWS.2

wsmo:WebService

SWS.3

wsmo:Goal

G.1

wsmo:WebService

SWS.1

wsmo:MedWS

SWS.1.1 Comp. Sim.

(1)

(2)

(4)

(5)

(3)

Similarity-based service matchmakingImplementation based on WSMO/IRS-III

� Implementation: Web Service Modelling Ontology (WSMO) & SWS environment IRS-III


Similarity-based service matchmakingImplementation based on WSMO/IRS-III

� Implementation: Web Service Modelling Ontology (WSMO) & SWS environment IRS-III

� WSMO Mediator: computation of similarities between given request (WSMO Goal, G1) and

set of x associated SWS (SWS1..SWSx):

� Limitation: suitability of service computed based on instance similarities

(=> current work: integration into “real” two-fold matchmaking)

wsmo:Mediator

Med.1

wsmo:WebService

SWS.2

wsmo:WebService

SWS.3

wsmo:Goal

G.1

wsmo:WebService

SWS.1

wsmo:MedWS

SWS.1.1 Comp. Sim.

(1)

(2)

(4)

(5)

(3)

( )

1

11

)(

),(),(

−

=−

==∑

n

dist

SWSGDistSWSGSim

n

k

k

jiji


� Uses representational approach (MS, similarity-based WSMO Mediator)

� Retrieval of distributed video resources

(provided within EU FP7 IP NoTube - http://notube.tv)

� Keyword-based searches across Web services exposing video repositories

� BBC Backstage (news feed) [ http://backstage.bbc.co.uk/ ]

� BBC Programmes RDF [ http://api.talis.com/stores/bbc-backstage ]

� Open Video [ http://www.open-video.org/ ]

� OU channel on YouTube [ http://www.youtube.com/ou ]

� YouTube (mobile feed) [ http://www.youtube.com/ou ]

� Similarity-based service discovery for given request

Semantic mediation through MSPrototypical application



SWS1:OU-youtube

O1:Purp O1:Env

SWS2:bbc-programmes

O2:Purp O2:Env

SWS3:open-video

O3:Purp O3:Env

SWS4: bbc-backstage

O4:Purp O4:Env

M62={v1, v2}

SWS5: mobile-youtube

O5:Purp O5:Env

MS2 Environment SpaceMS1 Purpose Space

SWS6: get-video-request

M61={v1, v2, v3}

WS1:OU-youtube

WS2:bbc-programmes

WS3:open-video

WS4:bbc-backstage

WS5:mobile-youtube



SWS1:OU-youtube

O1:Purp O1:Env

SWS2:bbc-programmes

O2:Purp O2:Env

SWS3:open-video

O3:Purp O3:Env

SWS4: bbc-backstage

O4:Purp O4:Env

M62={v1, v2}


O5:Purp O5:Env



M61={v1, v2, v3}

WS1:OU-youtube

WS2:bbc-programmes

WS3:open-video

WS4:bbc-backstage

WS5:mobile-youtube



SWS1:OU-youtube

O1:Purp O1:Env

SWS2:bbc-programmes

O2:Purp O2:Env

SWS3:open-video

O3:Purp O3:Env

SWS4: bbc-backstage

O4:Purp O4:Env

M62={v1, v2}


O5:Purp O5:Env



M61={v1, v2, v3}

WS1:OU-youtube

WS2:bbc-programmes

WS3:open-video

WS4:bbc-backstage

WS5:mobile-youtube

{(p1*information, p2*education, p3*leisure)} = CS1 {(p4*resolution, p5*bandwidth)} = CS2


SWS1:OU-youtube

O1:Purp O1:Env

SWS2:entertain-youtube

O2:Purp O2:Env

SWS3:open-video

O3:Purp O3:Env

SWS4: bbc-backstage

O4:Purp O4:Env

M62={v1, v2}


O5:Purp O5:Env



M61={v1, v2, v3}

WS1:OU-youtube

WS2:entertain-youtube

WS3:open-video

WS4:bbc-backstage

WS5:mobile-youtube


� Requests (WSMO Goals) via AJAX-based UI

� Consist of:

� Input parameters: set of keywords

� Assumption: defined through dynamically created instances

(based on measurements describing purpose and environment)

� Similarity-based SWS discovery based on WSMO mediator


Demo

SWS1:OU-youtube

O1:Purp O1:Env

SWS2:entertain-youtube

O2:Purp O2:Env

SWS3:open-video

O3:Purp O3:Env

SWS4: bbc-backstage

O4:Purp O4:Env

M62={v1, v2}


O5:Purp O5:Env



M61={v1, v2, v3}

WS1:OU-youtube

WS2:entertain-youtube

WS3:open-video

WS4:bbc-backstage

WS5:mobile-youtube


Summary:

� Two-fold approach: considering semantic-level mediation as implicit element of SWS

matchmaking

� Mediation approach based on (instance) similarity-computation

Issues:

� Matchmaking purely based on instance similarities

(=> current work: integration into “real” two-fold matchmaking)

� Similarity-calculation requires overlapping MS and measurable quality dimensions

� Additional representational effort => future work: evaluation

ConclusionsSummary & discussion


Thank you!

E-mail: [email protected]

Web: http://people.kmi.open.ac.uk/dietze

Dietze Aswc 2009 Final

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