Service Value Properties for Service Ecosystems: A Reference Model and a Modeling Guideline

Abstract

With the rise of service-oriented computing and web service ecosystems, services and their electronic descriptions become crucial to foster signi cant value propositions toward potential service consumers. While there exist ample technical speci cations to describe web services, conceptual approaches are rare. On top of this, an alignment between business models and information technology is lacking. This paper is a step toward this direction in that it o ers a reference model to classify service value descriptions depending on their purpose, presents a generic model for service properties, proposes two meta models for conceptual modeling, and nally introduces a modeling guideline.

Keywords

• service description
• reference model
• service ecosystems

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Tertiarisation describes a structural change in developed countries concerning the sectoral composition. Countries shift from an industry economy toward a service economy. Drivers of this change include Globalization, technological change, and an increasing demand for services [ 24 ]. Considering this trend, it becomes clear that services and the service economy play an important role in today's and tomorrow's business. In line with this trend, service ecosystems emerge, such as eBay, Google Base, Amazon.com, SalesForce.com, and SAP Business by Design. The vision of service ecosystems is an evolution of service orientation and takes services from merely integration purposes to the next level by making them available as tradable products on service delivery platforms [ 3 ]. They aim at trading services over the Internet between di erent legal bodies, compose complex services from existing ones, and IT-supported service provisioning [ 11 ].

Figure 1 depicts the steps involved in service trade: (1) service proposition, (2) service discovery & selection, (3) service negotiation & contracting, and (4) service monitoring & pro ling (cf. [ 15 ]). Midst service proposition, service providers advertise their services toward potential consumers, whereas during discovery &

Value

Exchange (S. Usage)

Value

Exchange (S. Usage)

Service

Proposition

Service

Negotiation & Contracting

Service

Discovery & Selection

Service

Negotiation & Contracting

Service Market Place Monitoring

Profiling

Service Consumer

selection, service consumers specify their service preferences toward providers. In case a service consumer selects an appropriate service, providers and consumers negotiate and nally agree on service levels (SLA) which are monitored throughout value exchange. In the event service levels are not met, compensations must be triggered. During service pro ling, valuable information on services' performance is stored, which is gathered while value exchange and monitoring.

In order to enable service trade, a shared and common understanding of services must become available. Nonetheless, no established language exists to de ne, to agree on, and to monitor service properties [ 15 ]. On top of that, Booms and Bittner [ 4 ] argue that services are di erent to goods, that is services are intangible, and thus, can neither be stored, transported, nor resold. Goods are produced at some point, stored, and eventually consumed at a later point. In contrast, production and consumption of services take place at the same time. Goods can be transported from one point to another. Services, on the other hand, are consumed at customers' locations, thus, production and consumption happen in one place. Whereas goods can be resold, services' outcome cannot be sold to another party. Additionally, services can hardly be standardized, since service experience is unique and depends on the individual expectations.

While ample technical speci cation exists to describe web services, conceptual notations to elicit business-relevant domain knowledge are lacking [ 28 ]. Suitable technical speci cations for web service descriptions include: (1) Web Service Description Language (WSDL) [ 25 ], (2) Web Ontology Language for Services (OWL-S) [ 16 ], (3) Web Service Modeling Ontology (WSMO) [ 26 ], and (4) Service Level Agreements for Web Services (WSLA) [ 13 ], just to name a few. Currently, semantic concepts to describe web services base on formal approaches, such as rst-order logic and predicates. This hinders domain experts to describe services with these concepts. A more sophisticated approach must become available. Recent work concentrates on the business service modeling discipline with a focus on how to formalize the relationship between business operational requirements and to implement them with service-oriented architectures (cf. [ 5 ]). However, the focus of these approaches lies in business process transformation [ 22 ]. No attempt has been made for service value descriptions.

This paper contributes in that it explores the conceptual gap of service value modeling. It o ers a reference model to classify service value descriptions, introduces a generic property model, proposes two meta models for conceptual modeling, and nally presents a modeling guideline.

The remainder of this paper is structured as follows: section two discusses important work which is related to the proposed solution. Whereas section three suggests a reference model, section four o ers a generic model that speci es how to model value descriptions. Section ve introduces two meta models with speci c properties which address what properties are of signi cance. Following this, section six brings out a modeling guideline to support a continuous modeling process. Finally, section seven concludes this work as well as o ers prospects about future work. 2

Related Work

Prior to dive into the reference model and the service value properties, this section discusses available work in the area of conceptual service descriptions.

Baida et al. [ 2 ] provide a study of di erent semantics for the terms: service, web service, and e-service from three di erent perspectives: Computer Science, Information Science, and Business Science. Currently, there is no common understanding of the term service in the di erent research areas. Consequently, they provide de nitions for real-world services, e-services and web services.

Papazoglou [ 23 ] describes an extended service-oriented architecture which comprises a basic service description. It includes the aspects: service capability, service interface, service behavior, and service quality attributes.

Oaks et al. [ 17 ] write about the lack to specify service capabilities, that is, what services, or agents, can do. They o er a structured and machine interpretable capability description. This approach will be of help to specify a services functional properties.

Complementary to Oaks et al., O'Sullivan [ 21 ] presents a wide range of quality attributes to describe real-world services. These attributes include availability, obligations, price, payment, and discounts, just to name a few. This property set is the main source for the value model which is shown in section 5.2. Business Process Models

Deployment Artifacts Software Environments a) Process Description

BOV FSV

Business Models

Analog to the proposed solution in this paper, the aforementioned approaches acknowledge the existence of a service description with its di erent aspects. Furthermore, they elaborate on speci c dedicated facts. On the other hand, the proposed solution in this paper goes beyond these disjoint approaches in that it o ers a general method which addresses every aspect of a service description. Additionally, it suggests means to bridge the gap between business speci cations and information technology. 3 This section proposes a reference model to di erentiate between service value description modeling phases. It is based on the open-EDI reference model [ 10 ], work of Dorn et al. [ 5 ], and Scheithauer et al. [ 28 ].

Whereas technical speci cations aim to describe services themselves, this work concentrates on the value services o er. Value descriptions formalize services' value and are composed of value properties, which support the phases of service trade. Such a description is considered as an external view on services [ 28 ], unlike a process description, which depicts an internal view on services' behavior.

The open-EDI reference model [ 10 ] distinguishes between the Business Operation View (BOV) and the Functional Service View (FSV). BOV comprises business data semantics as well as business transaction rules, such as agreements and obligations between partners. FSV on the other hand, focuses on information technology which includes interfaces, functional capabilities, and protocols. Dorn et al. [ 5 ] add subtle re nements to the open-EDI reference model, which gure 2a shows. They re ne BOV into business models and process models. Business models express value exchange between di erent actors and business analysis. Process models represent how each actor realizes value exchanges. Likewise, they re ne FSV into deployment artifacts and software environments. Deployment artifacts address implementations of business processes with technical speci cations, e.g., BPEL [ 1 ]. Software environments describe runtimes to execute technical artifacts. This re ned model serves as a classi cation system for concepts and modeling notations as well as to de ne means to bridge the di erent layers. It is important to note that the re ned open-EDI reference model by Dorn et al. focuses mainly on process descriptions. Hence, the reference model for value descriptions adepts subtle changes (cf. gure 2b). Scheithauer et al. [ 28 ] argue that value properties in the business model layer own a strategic semantic and take into account services' nal purpose and context. The next layer changes from process model to value model to re ect the actual modeling purpose of value descriptions. Value properties on this layer re ect a rm establishment with concrete values. The result is a value proposition toward potential customers. Deployment artifacts describe technical-related speci cations to implement value properties.

The following sections employ this reference model. Section 4 o ers a metameta model for all reference layers. Section 5 present speci c meta models for the business model layer and the value model layer.

The following subsections introduce brie y available approaches and technical speci cations for each layer of the reference model, which are shown in table 1. However, the software environment is omitted here, since it is out of scope of the proposed solution. 3.1

Business Model This section elaborates on the Business Model Ontology (BMO) and the e3 value model. Both approaches are suitable for the reference model's business model layer. Evidence for this is found here [ 5, 14, 27, 28 ].

BMO [ 20 ] is an ontology to accurately describe companies' business models. Osterwalder did an exhaustive literature analysis of existing business model definitions and theories as well as some real-world case studies in order to build and to evaluate the ontology. The author's main in uence is the work from Kaplan and Norton [ 12 ] about balanced score cards. The ontology's complexion is that of pillars, building blocks, and attributes. The rst tier nodes depict the pillars, the following nodes represent the nine building blocks. The third tear nodes are attributes for each building block. Osterwalder [ 20 ] provides a far more detailed description.

Gordijn et al. [ 8 ] argue that current requirement engineering methodologies are inadequate for the e-commerce domain, and hence, develop the e3 value model. e3 value model o ers a structured approach, to gather requirements for e-commerce applications. It includes three levels of abstraction and a six steps process for guidance. The three levels of abstractions are: (1) e-business model development, (2) e-business process design, and (3) software architecture requirements. Moreover, they provide six steps to guide the requirement creation process: (1) identi cation of actors in the e-commerce process, (2) construction of the list of the relevant value activities, (3) de nition of the associated value ports, interfaces, and value object types, (4) allocation of the value activities to the actors, (5) analysis of the trade-o s occurring in the alternative business models, and (6) tracking down the associated implications for requirements on the information systems architecture. 3.2

Value Model This section introduces the service property model [ 28 ], which is appropriate for the value model layer.

Scheithauer et al. [ 28 ] investigate valid service properties for service ecosystem, available modeling notations for service properties, and an appropriate framework in order to categorize modeling notations according to the needs of the di erent roles involved in the service engineering process.

The motivation to nd valid service properties is to describe services in such a way to allow aimlessly service trade over the Internet. It is envisioned that these properties support service proposition, discovery, selection, contracting, and monitoring in service ecosystems. In order to elicit valid service properties, the authors investigate available literature and analyze proposed properties, whereas work from O'Sullivan [ 21 ] is the main source. The result are 15 service properties and their relationships. For a better understanding and readability these properties are grouped into the following categories: (1) functionality, (2) nancial, (3) legal, (4) marketing, and (5) quality.

The authors nd the Zachman framework's perspectives as appropriate means to categorize available modeling notations. They argue that the origin descriptions address the internals of a solution, which is not su cient for service ecosystems. Rather, it is required to model the external view of services. Therefore, they motivate another description for the Zachman framework: service description. The basic descriptive model is that of properties and values and is valid for all perspectives in the Zachman framework. Bene ts include: (1) integration of service description modeling into the whole service engineering process, (2) categorization of available notations for each perspective, (3) discovery of missing service description notations, (4) recognition of overlaps, and (5) rst deliberations on how to bridge di erent perspectives. 3.3

Deployment Artifacts The following paragraphs shortly present available speci cations for the deployment artifacts layer.

The Web Service Modeling Ontology (WSMO) [ 26 ] is an ontology dedicated to web services. Its main elements include: (1) ontologies, (2) web services, (3) goals, and (4) mediators. The ontology element codi es domain knowledge, which is used by all other elements. Web services' capabilities are expressed with pre- and postconditions to describe services' value o ering. On the other hand, goal elements formalize desired value. Finally, mediator elements are means to overcome interoperability problems between other WSMO elements.

The Semantic Markup for Web Services (OWL-S) [ 16 ] is an upper ontology and base on the Web Ontology Language (OWL). It aims to describe web services in a semantic manner to enable automatic web service discovery, automatic web service invocation, and automatic web service composition and interoperation. OWL-S de nes four main elements. The service element is the root element. The service pro le element represents a service's functionality. The service grounding element discloses how to access the service. This is a bridge to a WSDL document. Finally, a service model element describes how a service works in terms of parameters and process descriptions.

Semantic Annotations for WSDL and XML Schema (SAWSDL) [ 6 ] o ers a way to annotate WSDL documents with semantic annotations. Whereas OWL-S brings its own means of grounding, WSMO uses SA-WSDL to do so.

Web Service Description Language (WSDL) [ 25 ] is an XML speci cation to describe web services as a set of message types, message formats, port types, operations, and protocol bindings. 4

Service Value Properties

This section de nes the value description and its re nement into value properties, and eventually proposes a generic model for value properties and is considered as a meta-meta model (cf. section 5).

Baida et al. de ne services in general as . . . business activities that often results in intangible outcomes or bene ts; they are o ered by a service provider to its environment" [ 2 ]. This paper refers to intangible outcomes and bene ts with the term value. Scheithauer et al. [ 28 ] de ne a service value description as an external view on services to describe a service's proposition [ 9 ] a company o ers toward its customers. They re ne value descriptions into a collection of properties and their values.

This paper adds a subtle re nement to this de nition in that it introduces a generic model for value properties. It is generic for it is capable to express properties from di erent approaches, and hence, provide a common semantic for value properties. This common semantic harmonizes di erent approaches (lessens the heterogeneity) and it enables to compare individual properties. M := fMQuantitative S MQualitativeg MQuantitative := fCurrency, Granularity, Percentage, Time, . . . g De nition 1 (Property). A property p 2 P is de ned over the alphabet (vc 2 V C; m 2 M ) with the set of value classes VC and the set of metrics M. V C := fSingle Value, Range Value, . . . g

MQualitative := f(In-)tangible, Text, Condition, . . . g A property either has an exact value or a value range. For example, a service provider might settle for an exact price (exact: 5.00), but prefer to de ne a service's availability with a range (min: 0.995; max: 0.998). Metrics, on the other hand, add semantic to a property. In general, metrics are distinguished between qualitative and quantitative characteristics. However, it is possible to further re ne metrics (e.g. Quantitative Metric ! Currency ! fEURjUSDjAUSg). A price property, for example, is de ned as Price = (Single Value, Currency Metric).

De nition 2 (Property Bundle). A property bundle pb 2 P B is de ned as (P C) with the set of property compositions PC.

Property bundling supports property nesting. Hence it is possible to combine properties into more complex properties. In fact, a value description is a property bundle.

De nition 3 (Property Composition). A property composition pc 2 P C is de ned over the alphabet (p 2 P _ pb 2 P B; c 2 C) with the set of cardinalities C. C := f0 : 1; 1 : 1; 0 : ; 1 : g.

A property composition element combines either a property or a property bundle with a cardinality to support property bundling. For example, a value o er as de ned by Osterwalder [ 20 ], is represented as a property bundle which is re ned into the property compositions (Price Level; 1:1) and (Target Customer; 1: ). 5

Meta Models for Value Descriptions This section presents two meta models, which integrate into the reference model's business layer and value layer, respectively. Both meta models build on the generic property model (cf. section 4). The graphical notation shows property bundles (PB) as rectangles with no attributes, properties (P) as rectangles with the attributes value class and metric, and property compositions as directed edges. 5.1

Business Meta Model The Business Model Ontology (BMO) [ 20 ] as well as the e3 value approach [ 7 ] form the basis for the business meta model.

The resulting business model selects only speci c concepts which contribute to the value description (cf. [ 14, 27, 28 ]). These include: (1) value o er, (2) distribution channel, (3) target customer (4) relationship, and (5) revenue model.

Business Model + Author + Version + Created + LastModified

1:1

Value Object : P + VC : Single Value + M : Free Metric Value Object Type : P 1:1 + VC : Single Value + M : (In-) Tangible Metric

Reasoning : P ++ VMC::SStrinugctleurVeadluTeext M.

Value Level : P ++ VMC::SStrinugctleurVeadluTeext M.

Price Level : P ++ VMC::SStrinugctleurVeadluTeext M.

Life Cycle Step : P ++ VMC::SStrinugctleurVeadluTeext M.

0:* 1:1 1:1 1:1 Value Object Bundle : PB 1:*

Value Offer : PB 1:* Revenue Model : PB

1:* 1:* Customer Bundle : PB

1:* 1:* Distribution Channel : PB

Stream Type : P 1:1 ++ VMC::SStrinugctleurVeadluTeext M.

Pricing Method : P 1:1 ++ VMC::SStrinugctleurVeadluTeext M. 1:1 +TVaCr:gSeitngCluesVtaolmueer : P + M : Free Text Metric

Relationship : P 1:1 ++ VMC::SStrinugctleurVeadluTeext M. 1:1 ++CVMuCs:t:S.StBrinuugcytlieunrVgeadCluTyeecxlet M:.P

Reasoning : P 0:* ++ VMC::SStrinugctleurVeadluTeext M.

Value Level : P 1:1 ++ VMC::SStrinugctleurVeadluTeext M.

Price Level : P 1:1 ++ VMC::SStrinugctleurVeadluTeext M. Figure 3 shows the resulting meta model. The following paragraphs discuss each concept.

Value O er is the root element and bundles the following properties: reasoning, value level, price level as well as life cycle step. Moreover, it bundles the value object property bundle, the revenue property bundle, the customer property bundle, and the distribution channel property bundle. Reasoning describes in which way a service is valuable for targeted customers. Osterwalder [ 20 ] distinguishes three elementary characteristics: value is either created by using a service, reducing any kind of risk for targeted customers, or reducing customers' e orts. The value level states to what extent services distinguish themselves from o ers other companies. Osterwalder provides four possible classi cations: either a value o er is a commodity, an innovative imitation, an excellence, or an innovation. The price level expresses services' qualitative pricing strategy. Services are either o ered for free, for an economic (low) price, for an appropriate market price, or for a high-end price. The life cycle step formalizes when value is created during the service life cycle. Osterwalder explains the life cycle with ve steps: value creation, value purchase, value use, value renewal, and value transfer.

Value Object Bundle is the actual value which is exchanged by companies o ering services and companies consuming services. Evidence for this element is found by Osterwalder as well as by Gordijn. Its properties include the value object itself and the value object type. The type attribute tells whether the value object is tangible or intangible.

Revenue Model describes the transformation of value o erings into income. It comprises the following properties: stream type and pricing method as well as a link to the customer property bundle. The stream type property formalizes how income is generated. Possible stream types include: selling, lending, licensing, transaction cut, and advertising. The pricing method describes in which way a price is determined. According to Osterwalder, a price is either xed and is agnostic to the environment and customer characteristics, is di erential and depends on product as well as customer characteristics, or is market-based in that the price is determined dynamically between provider and customer.

Distribution Channel tells how companies deliver value to targeted customers. The element bundles the properties: reasoning, value level, price level, and customer buying cycle. The properties reasoning, value level, and price level have the same semantic as in the value o er bundle, and hence, these can be setup for each channel. The customer buying cycle tells which step the channel addresses. Osterwalder proposes four steps for the buying cycle: awareness, evaluation, purchase, and after sales.

Customer Bundle speci es customer segments. Segments base, for example, on geographical criteria. The relationship property depicts in detail the type of connection between companies and their target customers. The relationship element classi es target customers according to their equity goals. Osterwalder o ers three classes, namely acquisition, retention, and add-on selling. 5.2

Value Meta Model The value meta model base upon work from Scheithauer et al. [ 28 ] (cf. section 3.2). Figure 4 shows the resulting value meta model, which is curtated due to space limitations. The following paragraphs elaborate on each rst level property bundle.

Properties in the functionality category provide the service consumer with an understanding of what the service is actually providing and thus, what the consumer can expect from the service. Properties include capabilities along with value objects and service classi cations.

Financial properties comprise monetary related aspects, such as price, discounts, and payments as well as their interrelation [ 21 ]. Though the meta model does not show it, the price property comes in the variations: absolute price, ranged price, proportional price, and dynamic price. The discount property can be re ned into payment discounts and payee discounts.

The legal property bundle embodies properties which state terms of use. The properties are rights, obligations, and penalties. Whereas rights state what service consumer are allowed or expected to do with the service, obligations determine and settle the commitment for a service provider and a service consumer. The penalty property dictates compensation in case an obligation was not met by one party. Each obligation property relates to one penalty property to cover the e ects. Penalties are represented with semantically de ned terms.

The marketing property bundle allows promoting services toward potential customers. Properties in this bundle should both attract customers and establish a trusted relationship. A certi cation would provide a rather neutral view on a service provided by a third party. On the other hand, expert test ratings provide

Availability : P + VC : Range Value + M : Percentage Metric

Reliability : P + VC : Range Value + M : Percentage Metric

Latency : P + VC : Range Value + M : Percentage Metric

Throughput : P + VC : Range Value + M : Throughput Metric

Benefit : P + VC : Single Value + M : Benefit Metric

Certification : P + VC : Single Value + M : Institute Metric

Expert Test Rating : P + VC : Single Value + M : Institute Metric for

Service

Ecosystems Quality : PB 1:1

Functionality : PB 1:1 1:1 0:* 0:* 1:1 Legal : PB

0:*

Payment Bundle : PB a sub jective view on the service from an expert perspective. Service bene ts are the gained outcome of the service with respect to the potential service consumer.

Quality of services comprise: (1) latency, (2) throughput, (3) availability, and (4) Reliability. As aforementioned, service provisioning in service ecosystems is conducted over the Internet, technical properties of the network and the service itself can be of importance for service discovery and selection. 6

Mo deling Guideline

This section introduces an initial modeling guideline for value descriptions. It aims at bridging the business model and the value model layer by means of twelve abstract steps (cf. gure 5). The guideline is a result of the authors' practical experience as well as a deep knowledge in this research domain. Steps one to six support the modeling of the business model, whereas steps seven to twelve assist the modeling of the value model. 6.1

De ne

Business

Model The rst six steps support business strategists to transform a service idea into a tangible foundation for business strategists, business analysts as well as business owners to decide whether to implement a service or not (predetermined breaking point). The activities for this step include: (1) Establish exactly one value o er

IESSN LED SU OM B LEVUA LEDOM 1)1)EDsteafbinliesh VoanleueVOalfufeer

Offer 71) Defrinve Value Offer 2) DCeotnesrtmituinte KeyVBaulusieness

AOcbtijveitcietss 8) Model 1) Define Functional Value Offer Properties 32) Determine KeyTBaurgseintess CAucstiovimtiesrs 9) Model 2) Determoinfe Quality KeSyeBruvisciensess

Activities Properties 4) Determine 2) Determine RelaBtiuosninsheisps Key for each Activities Customer 2)1D0)eMteormdeinle KeMyaBrkuestinegss PArcotpiveirtiteiess 52) Determine KDeyistBriubsuitnioenss CAhcativnintiels 2)1D1)eMteormdeinle KeyLBeugsainless PArcotpiveirtiteiess

6) Setup 2) Determine appropriate Key Business

Revenue Activities

Models 2)1D2)eMteormdeinle KeFyinBaunsciniaelss PArcotpiveirtiteiess with its direct properties, (2) constitute appropriate value objects, (3) determine one or more target customers, (4) determine exactly one relationship for each target customer, (5) determine one or more distribution channels, and nally (6) setup one or more revenue models.

In order to identify the concepts for this model, a deep understanding of the business domain as well as marketing is necessary. The outcome of this step is an instance of the model described in section 5.1: a value o er which describes the service from a strategic perspective. The steps six to twelve support business analysts to conceptualize a value o er, hence determine how to implement it. The outcome of a value model serves as means for communication and as a support for decisions. It is neither technical nor platform-dependent. Furthermore, it is a starting point for a transformation into technical speci cations [ 29 ]. The goal is to operationalize aspects from the strategic perspective into a value proposition which is available to potential customers. Hence, all strategic artifacts with internal knowledge must be revealed, including the value level, the target customer, the revenue model, and the and the price level.

The general order of value modeling is: (1) Value O er, (2) Functionality, (3) Quality, (4) Marketing, (5) Legal, and nally (6) Financial. Tables 2 shows a mapping between business model properties and value model properties. This light-weight mapping between the business model and the value model eases the value description modeling.

The challenges involved in value modeling are manifold: transformation of abstract value o ers into concrete capabilities, de nition of quality of service properties, establishing marketing concepts, investigating legal implications, and calculating nancial numbers. The outcome is an instance of a value model (cf. section 5.2). 7

Conclusion & Future Work

Service Ecosystems are market places to trade services over the Internet, which are pushed by Globalization and technological change. Considering this trend, it becomes clear that services and the service economy play an important role in today's and tomorrow's business. Consequently, services and their electronic descriptions become crucial to foster signi cant value propositions toward potential service consumers. While there exist ample technical speci cations to de ne web service value descriptions, conceptual approaches are rare. On top of this, an alignment between business models and information technology is missing.

This paper contributes in that it explores the conceptual gap of service value modeling. It o ers a reference model to classify service value descriptions, introduces a general property model, proposes two meta models for conceptual modeling, and nally presents a modeling guideline. Business information science bene ts from the incorporation of actual studies in the areas of service value descriptions and conceptual modeling. The modeling guideline enables industries to apply the framework. Furthermore, the whole solution complements the Inter-enterprise Service Engineering (ISE) framework [ 14 ].

This work's major limitation is a missing veri cation of the presented approach. This issue will be addressed in the next step of the Theseus / TEXO research project [ 11 ]. Ongoing work includes tool development for the proposed meta models (cf. section 5) and improvements in the alignment between the business model and the value model. Future work will address Electronic Business using eXtensible Markup Language (ebXML) [ 18 ] and Universal Description, Discovery and Integration (UDDI) [ 19 ]. It is envisioned to automatically generate artifacts for these speci cations. Likewise, the approach will be extended toward semantic web services. The proposed value model will be codi ed with an ontology language and an algorithm needs to be invented which transforms a value model instance into a semantic web service description.

Acknowledgments

This project was funded by means of the German Federal Ministry of Economy and Technology under the promotional reference \01MQ07012". The responsibility for the content of this publication lies with the authors

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