Ten years of service research from a computer science perspective

Jorge CardosoCISUC/Dept. Informatics Engineering, University of Coimbra, Portugal

Karlsruhe Service Research Institute, Karlsruhe Institute of Technology, Germanyjorge.cardoso@kit.edu; jcardoso@dei.uc.pt

Ten years of service research from a computer

science perspective

Departamento de Engenharia InformáticaFCTUC FACULDADE DE CIÊNCIAS E TECNOLOGIA da

UNIVERSIDADE DE COIMBRA

10-04-2023 Ten years of service research from a computer science perspective 2

…It has been more than 10 years since a strong research stream on services started from the field of computer science. The main trigger was without a doubt the introduction of the Web Service Description Language (WSDL), a specification to represent a piece of software functionally which could be remotely invoked. Nonetheless, this was only the “tipping point”. The generalized interest on this new development was followed by interesting topics of research on the application of semantics to enhance the description of services, the composition of services into processes, the analysis of the quality of services, the complexity of processes supporting services, and the development of comprehensive service description languages. This seminar will provide an overview of the main research topics around services and will glimpse at a new research field on the analysis of service networks... Karlsruhe, 15 Jun 2013

Jorge Cardoso

Abstract

04/10/2023 Ten years of service research from a computer science perspective 3

Semantic Web Services

Semantic Web ServicesService DescriptionsQuality of Service Process ComplexityInternet of Services Service Networks

A simple problem to solve

Client Server

Request message010101110100101

Response message0101001011101001

Internet

Service Oriented Computing II – SS 2013

Almost 15 years to “Solve”

• Web services (WSDL/SOAP)• Java Remote Method Invocation (Java RMI)• Distributed Component Object Model (DCOM)• Common Object Request Broker Architecture (CORBA)• Remote Procedure Calls (RPC)• Socket Programming (SP)

24.04.2013

CORBA (1992) DCOM (1996)SUN RPC (1985)

Berkeley SP (1983)

JAVA RMI (1996) WSDL/SOAP (2000)

The Problem (2000)

Response message0101001011101001

Request message010101110100101

Intraorganizational

The web

The Search & Matching Problem

Previous Approaches

• Keyword-based

• Information Retrieval Techniques

The Idea (2002)

Semantic Matching

Ontology with background knowledge

Cardoso, J. and Sheth, A. Semantic e-Workflow Composition. In Journal of Intelligent Information Systems (JIIS), Vol. 21 (3): 191-225, 2003.

Example of an ontology

Semantic Descriptions• Web Service Technology

– Automated discovery, selection, composition,

– Web-based execution of services

• Semantic Web Technology – Allow machine supported

data interpretation– Ontologies as data model

• Semantic Web Services – as integrated solution for

realizing the vision of the next generation of the Web WSDL

Ontology

Semantic Matching = Ontology

Temporal-Entity

TimeInterval

Time-Point

Date Time

TimeDomain

Scientific-Event

Calendar-Date

{absolute_time}

{hour, minute, second}

{millisecond}

{year, month, day}

{dayOftheWeek, monthOftheYear}

Temporal-Entity

TimeInterval

Time-Point

Date Time

TimeDomain

Scientific-Event

Calendar-Date

{absolute_time}

{hour, minute, second}

{millisecond}

{year, month, day}

{dayOftheWeek, monthOftheYear}

ST1,2 (output) SO1,2,3,4 (input)

Time ontology Time ontology

A2A2A1A1

Calendar-Date

Similarity ?

Web Service Web Service

Concepts from the same Ontology a) Concepts are the same (O=I)b) Concept I subsumes concept O (O>I)c) Concept O subsumes concept I (O<I), or d) Concept O is not directly related to

concept I (OI).

Car subsumes 2-Wheel drive

Semantic Matching <> Ontology

IOIOSimilarity

IOSemS

|)(|,1

|)()(|*

|)()(|

|)()(|),('

IpOpIOsimilarity

O subsumes I

(Remember)Car subsumes 2-Wheel drive

I subsumes O

O has no subsumes relation with I

p(X) = properties of X

Based on Tversksy (1977) feature model

Cardoso, J. Discovering Semantic Web services with and without a Common Ontology Commitment. In The 3rd International Workshop on Semantic and Dynamic Web Processes (SDWP 2006),

Other aspects to match

A2A2A1A1

Calendar-Date

Similarity ?

Web Service Web Service

]1..0[, and

],1..0[).,.().,.(

sdADVsdRSynDSsnADVsnRSynNS

ADVRtySynSimilar

3 ),,(QoSdimD*),,(QoSdimD*),,(QoSdimD

),ty(OpSimilari

yreliabilitADVRcostADVRtimeADVR

3 ),,(QoSdimD*),,(QoSdimD*),,(QoSdimD

),ty(OpSimilari

yreliabilitADVRcostADVRtimeADVR

),,(dcd*),,(dcd*),,(dcd),,QoSdimD( 3maxavgmin dimADVRdimADVRdimADVRdimADVR

))(.min(

|))(.min())(.min(|1),,(dcdmin dimqosR

dimqosRdimqosADVdimADVR

• Quality of Service

Cardoso, J.; Miller, J. A.; Sheth, A.; Arnold, J. and Kochut, K. Quality of service for workflows and web service processes. In Journal of Web Semantics, Vol. 1 (3): 281-308, 2004.

Another matching problem…

10000 *

The (same) Idea

Semantic Matching

Ontology with background knowledge

Cardoso, J. and Sheth, A. Semantic e-Workflow Composition. In Journal of Intelligent Information Systems (JIIS), Vol. 21 (3): 191-225, 2003.

Semantic Process Composition

HotelReservation

TravelReservation

Get UserInformationGet User

Information

Get ConferenceInformation

Conference

Employee ID

DateDuration

User NameAddress

ItineraryItinerary

Conference RegistryService

Hotel Reservation Service

A BStart End

ADV2ADV2 ADV3

0.990.34 0.74

Match FunctionADV1ADV10.14

0.980.68

0.430.31

f(R, ADV1) f(R, ADV2) f(R, ADV3)

Process

04/10/2023 Ten years of service research from a computer science perspective

Semantic Web Services• Cardoso, J. The Semantic Web Vision: Where Are We?. In IEEE Intelligent Systems, Vol.

22 (5): 84-88, 2007.• Cardoso, J. The Semantic Web: A mythical story or a solid reality. In Metadata and

Semantics, pages 253-257, Springer, Heidelberg, 2008.• Cardoso, J.; Miller, J. A. and Emani, S. Tutorial Lectures: Web Services Discovery

Utilizing Semantically Annotated WSDL. In 4th International Summer • Patterson, R.; Miller, J. A.; Cardoso, J. and Davis, M. Bringing Semantic Security to

Semantic Web Services. In The Semantic Web: Real-World

Remember our problem…

We were looking for apples Web Services

ServiceEndpointBindingInterfaceOperationTypes

(…a procedure or function…)

Service Description

What about more complex services?

Fromapples to morecomplex fruits

In other words

CLOUD SERVICESComplex interfacesDependencies between callsPricing, legal aspects, SLASOAP, REST, etc.

INTERNET/WEB-BASED SELF-SERVICE TECHNOLOGY (I/W-SST)

WEB-BASED SERVICESHUMAN-COMPUTER INTERACTIONUSER INTERFACECUSTOMER EXPERIENCE

WEB SERVICESSimple invocationsSimple atomic, singular servicesIntra-organizationsMachine-machine interaction

The Idea (2008)

US DLB us ines s

Operational

Tec hnic al

OperationsF unctionality

R es ources…

P roviderC ons umerB undlingMarketingL egal…

P rotocolsAddress

P orts…

Tec hnic al

Made for c omputers (S O A) Made for people (IoS )

AddressP ortArgumentsData type… US DL

B us ines s

Operational

Tec hnic alUS DL

B us ines s

Operational

Tec hnic al

OperationsF unctionality

R es ources…

P roviderC ons umerB undlingMarketingL egal…

P rotocolsAddress

P orts…

Tec hnic al

Made for c omputers (S O A) Made for people (IoS )

AddressP ortArgumentsData type…

Cardoso, J. Service Engineering for Future Business Value Networks. In Tenth International Conference on Enterprise Information Systems (ICEIS 2008), pages 15-20, Barcelona, Spain, ISBN: 978-989-8111-37-1, 2008.

Services Description (2009-13)

* advertise and discover services* selection, composition and interoperation of services

Cardoso, J.; Barros, A.; May, N. and Kylau, U. Towards a Unified Service Description Language for the Internet of Services: Requirements and First Developments. In IEEE International Conference on Services Computing, 2010.

Service Oriented Computing II – SS 2013

• Blueprint– line of interaction

• E.g. face-to-face actions between employees and customers

22.05.2013

USDL:INTERACTIONPOINT

NAME:usdl:InteractionPoint DESCRIPTION:rdfs:comment """<p>An InteractionPoint represents an actual step in accessing and performing operations of the service. On a technical level this could translate into calling a Web Service operation.On a professional level, it could mean that consumer and provider meet in person to exchange service parameters or resources involved in the service delivery (e.g. documents that are processed by the provider).An InteractionPoint can be initiated by the consumer or the provider. Since InteractionPoints may take time and have an ordering with respect to other InteractionPoints, this is a subclass of TimeSpanningEntity. One can therefore express temporal relationships between InteractionPoints such as before or after. For richer expressions the time ontology constructs could be used.</p>"""@en .SUBCLASS:rdfs:subClassOf usdl:TimeSpanningEntity;

Resources

http://www.linked-usdl.org/ https://github.com/linked-usdl/

History• a-USDL/2009

– Initial version of USDL [CBM+2010] ready in 2009. – Later renamed to a-USDL (pronounced alpha-USDL). – http://www.genssiz.org/research/service-modeling/alpha-

• USDL/2011

– A W3C Incubator group was created USDL was adapted and extended based on industry feedback at the end of 2011.

– http://www.w3.org/2005/Incubator/usdl/

• Linked-USDL/2012--?

– In order to make the specification gain a wider acceptance, a version called Linked USDL emerged using Semantic Web principles. Its development is still in progress.

– http://linked-usdl.org/Cardoso, J.; Winkler, M. and Voigt, K. A Service Description Language for the Internet of Services. In First International Symposium on Services Science (ISSS'09), Leipzig, Germany, ISBN: 978-3-8325-2169-1, 2009.

Applications

Cloud Services

Consider cost, compatibility, space, speed, etc.

Decision Maker

Service Descriptions• Cardoso, J.; Binz, T.; Breitenbucher, Uwe; Kopp, O. and Leymann, F. Cloud Computing

Automation: Integrating USDL and TOSCA. In CAiSE, Springer, LNCS, Vol. , 2013.• Cardoso, J. and Miller, J. A Internet-Based Self-Services: from Analysis and Design to

Deployment. In The 2012 IEEE International Conference on Services Economics (SE 2012), IEEE Computer Society, Hawaii, USA, 2012.

• Cardoso, J.; Barros, A.; May, N. and Kylau, U. Towards a Unified Service Description Language for the Internet of Services: Requirements and First Developments. In IEEE International Conference on Services Computing, IEEE Computer Society Press, Florida, USA, 2010.

• Cardoso, J.; Voigt, K. and Winkler, M. Service Engineering for The Internet of Services. In Enterprise Information Systems, pages 15-27, Springer, ISBN: 978-3-642-00669-2 (Print) 978-3-642-00670-8 (Online), 2009.

• Cardoso, J.; Winkler, M. and Voigt, K. A Service Description Language for the Internet of Services. In First International Symposium on Services Science (ISSS'09), Leipzig, Germany, ISBN: 978-3-8325-2169-1, 2009.

The Problem

HotelReservation

TravelReservation

Get UserInformationGet User

Information

Get ConferenceInformation

Conference

Employee ID

DateDuration

User NameAddress

ItineraryItinerary

Conference RegistryService

Hotel Reservation Service

A BStart End

ADV2ADV2 ADV3

0.990.34 0.74

Match FunctionADV1ADV10.14

0.980.68

0.430.31

f(R, ADV1) f(R, ADV2) f(R, ADV3)

Process

How to evaluate the Quality of Service?

Does this slide look familiar !?-- 17 --

The Problem

t4t3 t8t1

PrepareSample

PrepareClones

CreateReport

Send Report

SequenceProcessing

Sequencing SendBill

xor xor

StoreReport

xorxor

How to evaluate the Quality of Service?

How much does it costs?How much time does it take?How reliable it is?

The Idea (2002)

QoSQoSQoSQoS

QoSQoS

t4t3 t8t1

PrepareSample

PrepareClones

CreateReport

Send Report

SequenceProcessing

Sequencing SendBill

StoreReport

xorxor

TimeCostReliabilityFidelity

Cardoso, J.; Miller, J. A.; Sheth, A.; Arnold, J. and Kochut, K. Quality of service for workflows and web service processes. In Journal of Web Semantics, Vol. 1 (3): 281-308, 2004.

Research Questions• Specification

– What dimensions need to be part of the QoS model for processes?

• Computation– What methods and algorithms can be used to compute, analyze,

and predict QoS?

• Monitoring– What kind of QoS monitoring tools need to be developed?

• Control– What mechanisms need to be developed to control processes, in

response to unsatisfactory QoS metrics?

QoS Estimation a) QoSDim(t) Designer AverageDim(t)

b) QoSDim(t) wi1* Designer AverageDim(t) + wi2* Multi-Workflow AverageDim(t)

c) QoSDim(t, w) wi1* Designer AverageDim(t) + wi2* Multi-Workflow AverageDim(t) + wi3*Workflow AverageDim(t, w)

d) QoSDim(t, w, i) wi1* Designer AverageDim(t) + wi2* Multi-Workflow AverageDim(t) + wi3* Workflow AverageDim(t, w) + wi4* Instance Workflow AverageDim(t,w, i)

QoS dimensions computed at runtime

Designer AverageDim(t) Average specified by the designer in the basic class for dimension Dim

Multi-Workflow AverageDim (t) Average of the dimension Dim for task t

executed in the context of any workflow

Workflow AverageDim(t, w) Average of the dimension Dim for task t

executed in the context of any instance of workflow w

Instance AverageDim(t, w, i) Average of the dimension Dim for task t

executed in the context of instance i of workflow w

Designer, multi-workflow, workflow and instance average

Basic class Distributional class Min value Avg value Max value Dist. Function

Time 0.291 0.674 0.895 Normal(0.674, 0.143) Cost 0 0 0 0.0 Reliability - 100% - 1.0 Fidelity.ai 0.63 0.81 0.92 Trapezoidal(0.7,1,1,4)

Task QoS for an automatic task (SP FASTA task)

Runtime, design time, between workflows, instances, etc.

QoS Reduction Rules• Sequential• Parallel• Conditional• Loop• Fault-tolerant• Network

(a) (b)

tli+ +

po1pl1ti… …

… …

T(tli) = ip-1

)(T it

C(tli) = ip-1

)(C it

R(tli) = )(Rp-1

)(R*)p-(1

F(tli).ar = f(pi, F(ti))

(a) (b)

+tbta t1n

pa1p1b

pa2p1n pb

tn T(t1n) = ni.1

pai * T(ti)

C(t1n) = ni.1

pai * C(ti)

R(t1n) = ni.1

pai * R(ti)

F(t1n).ar = f(pa1, F(t1), pa2, F(t2), …, pan, F(tn))

Stochastic Workflow Reduction (SWR) algorithm

G LkH I J

A B C D

E F N4

Process w

qos(x1,..,xn)

Sub-process w1

Sub- process w2

Sub- process w3

Apply a set of reduction rules to a process until only one atomic* task exists

For each rule applied, the process structure changes

After several iterations only one task will remain

The final task contains the QoS of the process under analysis

e.g. DNA Sequencing

How Complex is a Process?

Payroll

Human Capital Management

Purchasing

Customer Relationship Management

Supply Chain Control

Production and Site Logistics Execution

IT Service and ApplicationManagement

Process Componentat Business Partner

Enterprise Service Interaction (cross Deplyoment Unit)

Expense andReimbursement

Management

Direct Interaction (intra Deployment Unit)

Business Planning

InventoryProcessing

Project Management

RFQ Processing

Requisitioning

Supplier Invoicing

Catalogue Publishing

Catalogue Authoring

Payment

Due Item Management

Customer Invoicing

Financial Accounting

Deployment Unit

Production

Sales OrderProcessing

CustomerQuote

Processing

OpportunityProcessing

Goods andService

Acknowledgement

Service RequestProcessing

Customer InvoiceProcessing at

Supplier

Supplier InvoiceProcessing at

Customer

Payment OrderProcessing atHouse Bank

Purchase OrderProcessing at

CustomerSales OrderProcessing

atSupplier

CustomerInvoice

Processing

AccountingDue Item

Processing

Supplier InvoiceProcessing

RFQProcessing

PaymentProcessing

Bank statementcreation at bank

Opportunity /Customer Quote

Processing atSupplier

Time andLabour

Management

PersonnelAdministration

ServiceConfirmationProcessing

Service OrderProcessing

PurchasingContract

Processing

ActivityManagement

DemandPlanning

OutboundDelivery

Processing

CustomerReturn

Processing

updated on Jan 3rd 2007 (Jens Freund) -- interactions from dependent objects not included yet

Goods andService

Confirmationat Supplier

PaymentProcessing at

Business Partner

PurchaseRequest

Processing

ProjectProcessing

Internal RequestProcessing

Supply andDemandMatching

DemandForecast

Processing

CashManagement

ExternalProcurement Trigger

and Response

Inbound DeliveryProcessing at

Customer

Site LogisticsProcessing

ProductCataloguePublishing

ProductCatalogueAuthoring

CustomerRequirementProcessing

ProductionTrigger andResponse

In-HouseRequirementProcessing

MaterialInspectionProcessing

ProductCatalogue

Authoring atSupplier

ProductCatalogue

Authoring atCustomer

Expense andReimbursement

Management

Purchase OrderProcessing

CompensationManagement

BusinessPartner DataManagement

LockBox Filecreation at

provider

SettlementProcessing

at Clearing House

Source ofSupply

Determination

ProductionModel

Management

Product DataManagement

Process components not assigned to adeployment unit belong to foundation

LogisticsExecution

Control

PhysicalInventory

Processing

CustomerComplaint

Processing

InboundDelivery

Processing

Costing

EngineeringChange

Processing

LeadProcessing

External BankDirectory

Management

FinancialMarket DataManagement

Service RequestProcessing at

Provider

ServiceContract

Processing A

Processing ofProduct Tax

Declaration atTax Authority

Installed BaseData

Management

OrganisationalManagement

Resource DataManagement

Location DataManagement

Logistics Areaand StorageManagement

InspectionMaster DataManagement

Site LogisticsModel

Management

Price MasterData

Management

Process Component

FinancialAccounting MasterData Management

Requester

SoftwareProblemReporting

SAP SupportRequest

Processing

SAP ServiceDelivery

Processing

Provider

Service DeliveryProcessing at

FR EmployerRegulatoryCompliance

DE EmployerRegulatoryCompliance

US EmployerRegulatoryCompliance

CN EmployerRegulatoryCompliance

IT EmployerRegulatoryCompliance

GB EmployerRegulatoryCompliance

Input andOutput

Management

EmployeePayroll

Administration

Payroll Processing

Human CapitalMaster DataManagement

PayrollProcessing at

Provider

IT ChangeManagement

Logistic UnitData

Management

Data FlowVerification

IdentityManagement

BusinessDocument Flow

Processing

CampaignManagement

Balance OfForeign Payment

Management

InformationLifecycle

Management

DocumentManagement

RFQProcessingat Customer

Service OrderConfirmation

Processing atCustomer

Groupware

SystemAdministration

BusinessConfiguration

PaymentMaster DataManagement

SystemAdministration

at Provider

ExternalProduction Model

Processing

Further CashManagement

Relevant Component

Price Master DataManagement at

Customer

Due ItemProcessing At

Business Partner

Processing of EuropeanCommunity Sales ListReport at Tax Authority

Processing ofWithholding

TaxDeclaration atTax Authority

Bill Of ExchangeProcessing atHouse Bank

OutboundDelivery

Processingat Supplier

Sales ContractProcessing at

Supplier

Supplier InvoiceVerification

Exception Resolutionat Processor

TaxProcessingat Authority

CustomerProject Invoice

Preparation

Third Party ProcessComponent

DataMigrationSystem

Migration Adapter

Migration DataDispatching

The Idea (2005)

(1) while(x<100){(2) if (a[x] % 2 == 0) {(3) parity = 0; } else {(4) parity = 1;(5) }(6) switch(parity){ case 0:(7) println( “a[“ + i + “] is even”); case 1:(8) println( “a[“ + i + “] is odd”); default:(9) println( “Unexpected error”); }(10) x++; }(11) p = true;

Node Statement

MCC=e - n + 2, where e and n are the number of edges and nodes in the graph

Software Complexity Process Complexity

Cardoso, J.; Mendling, J.; Neumann, G. and Reijers, H. A Discourse on Complexity of Process Models. Second International Workshop on Business Process Intelligence, 2006.

Views on Process Complexity

Control-flow Complexity

}Pof splits-AND{

}Pof splitsOR{

}Pof splitsXOR{

ksplitAND

jsplitOR

isplitXOR

2n-1,where n is the fan-out of the split

Fan-out of the split

Cardoso, J. Business Process Control-Flow Complexity: Metric, Evaluation, and Validation. In International Journal of Web Services Research, Vol. 5 (2): 49-76, 2008.

Understandability

Which one is more difficult to understand?

The Idea (2006)

“… the average connector degree is the most convincing factor that relates to model understandability, followed by a model’s density”

Mendling, J.; Reijers, H. and Cardoso, J. What Makes Process Models Understandable?. In The 5th International Conference on Business Process Management (BPM 2007), 2007.

The average connector degree refers to the number of input and output arcs of a routing element

The ProblemService Engineering

The Idea (2008)

A model is an abstractionA model only focus on certain aspects

A model is created to describe a phenomena

A Service

Mental model

Cardoso, J. The Internet of Services. In Proceedings of the 4th International Conference on Software and Data Technologies , 2009

The Idea (2008)

TXT, VISIO, PPT description of services

Formal definition of functional/

non-functional requirements

(semantic) Interface, message,

format,data, etc

SAWSDL, WSDL, SOAP, WS-Policy,

XML Schema, XML, WSMO, etc

WP7/WP10

Scope Model{contextual}

Business Model{conceptual}

Logical Model{system}

Technical Model{physical}

Runtime{operational}

TXT, VISIO, PPT description

of the workflow

Formal definition of functional/

non-functional, BPMN

WS-Policy, WS-CDL, WS-CI,

WP7/WP10

Service Workflow

of data assets

Interrelations between semantic

data assets

Semantic data model

OWL, RDFS,XML Schema,

WP7/WP10

of organizational units

Organizational chart

Interaction between people and

service/processes

GUI between people and

services/processes. Security model

WS-policy

WP7/WP10

People

TXT, VISIO, PPT Goals and strategy

Business plan(rules and constraints)

Business rule model

RuleML, SWRL

WP7/WP10

Requirements Design Implementation

Method =Technique and Process

A sequence of actions

leading to some resultA Method

producesmodels

A specific construct

supporting a method

Underlying concepts (paradigm)E.g. service-oriented development

Preparation Market Market LunchDefinition

ISE Workbench

Executive

Manager

Process Architect

Business Analyst

Cardoso, J.; Winkler, M.; Voigt, K. and Berthold, H. IoS-Based Services, Platform Services, SLA and Models for the Internet of Services. In Software and Data Technologies, Springer. 2009.

The importance of networks

World Wide Web Social NetworksLinked Data

Financial/Political Networks Food chain NetworksRailway Network

…energy grids, water systems, wireless mobile networks...

Service descriptions

• Customers• Avis Scandinavia

• Supliers• Oracle 11g or IBM DB2 database

support services.

• Competitors • SalesForce.com Sales Cloud, Microsoft

On-Demand Dynamics CRM, and Oracle CRM OnDemand

• Complementors • Sage ERP and Sugar ERP Business

Suite are complementors of SugarCRM

[CPL+12] Cardoso, J.; Pedrinaci, C.; Leidig, T.; Rupino, P. and Leenheer, P. D Open semantic service networks. In The International Symposium on Services Science (ISSS 2012), pages 1-15, Leipzig, Germany, 2012.

The relationship problem• Given two services

– Does a relationship exists between them?

– What is the support for the relationship?

– What is the type of the relationship [Car13]?

– What is the direction of the relationship?

– What is the strength of the relationship?

[Car13] Cardoso, J. Modeling Service Relationships for Service Networks. In 4th International Conference on Exploring Service Science (IESS 1.3), pages 114-128, Springer, LNBIP, Porto, Portugal, 2013.

The relationship problem

Aggregation

Ten years of service research from a computer science perspective 57

The centrality problem• Given a node and its

neighbors– Popularity, power, collaboration

• (Traditional) degree centrality– A = 6

• How to calculate Service centrality? + aG+aF - bB - bC + cE + dD

Can it be proved?

10-04-2023

CustomersSupliersCompetitors Complementors

• Hypothesis– People near holes in a social

structure are at higher risk of having innovative ideas

• Level– Individual

• Leads to– Power, influence, money,

advancement, access, advantage

[Bur09] Burt, Ronald S, Structural Holes: The Social Structure of Competition, Harvard University Press. 2009.

Competitive advantage is a matter of access to structural holes in relation to market transactions [Bur09]

Structural hole (Burt)

• What are the implications for services?– Discover new markets– Evaluate the innovative

potential of organizations

Ten years of service research from a computer science perspective 59

The Idea (2012)

Open Semantic Service Relationship (OSSR)

• Service description• Relationship description• Follows Linked Data principles • Means for publishing and

interlinking distributed services

10-04-2023

Service System & Relationships The first steps …

[CPL+13] Cardoso, J.; Pedrinaci, C. and Leenheer, P. D Open Semantic Service Networks: Modeling and Analysis. In 4th International Conference on Exploring Service Science (IESS 1.3), pages 141-154, Springer, LNBIP, Porto, Portugal, 2013.

Thank You

for Listening

Ten years of service research from a computer science perspective

web service processes

qosdimd r

field of computer science

analysis of service

computer science perspective2

computer science perspective3

computer science perspective6

computer science perspective7

Technology

Computer games In Post PC perspective

Com 1013 Chapter 3 : Computer SoftwareApplication...

Troubleshooting Perspective & Computer Infestation.

Computer Systems A Programmer's Perspective 1

Introducing Computer Systems from a Programmer’s...

A Ten-Year Perspective: California Infrastructure Spending

Positive Accounting Theory: A Ten Year Perspective Watts...

The PPPL Perspective on Ten Year Planning

Smart Grid from Computer Engineering Perspective

PropTech; a two and ten year perspective

Computer Security -A Hacker's Perspective

Mobile Computer Usability: An Organizational Personality...

Scientific Writing The Computer Science Perspective Tom ...

The$PPPL$Perspective$on$Ten$Year$Planning$in ...

Perspective in Contemporary Computer Games · Perspective.....

Ten slides in Ten minutes - A Perspective on Organisational....