Hybrid Service Modeling in Enterprise Computing

Vedran Hrgovcic, Robert Woitsch BOC Asset Management GmbH

Vienna, Austria {firstname.lastname}@boc-eu.com

Dimitris Karagiannis University of Vienna

Department of Knowledge Engineering Vienna, Austria

dk@dke.univie.ac.at

Abstract— The Internet evolved to a generic platform and became fully pervasive infrastructure providing services anywhere and anytime. Hence the assumption is that any service requested by any business process is already provided somewhere in the Internet. This requires that services are conceptualized to fit descriptions of business process but on the same time rely on their technical specification, hence the semantic distance between business processes and service technology must be bridged. “Service modeling” has been identified as a promising concept to enable such semantic bridging. Each phase of Service Life Cycles is well supported by a range of service models. The research challenge of this paper is to introduce a holistic modeling framework that enables the use of hybrid service models to bridge larger semantic distances than by using only individual service models. The paper discusses the motivation, challenges as well as the conceptual and technical approach before introducing prototypes as a proof of concept.

Keywords: Service Modeling, Hybrid Modeling Framework, Metamodeling, Service Lifecycle

I. INTRODUCTION This paper discusses service modeling according to the

use of service models, the different approaches as well as the challenges and introduces the so-called hybrid modeling approach that enables the combination of different service models. Looking at publication statistics of IEEE, Springer and ACM publications in the field, an exponential growth of publications can be observed starting around 2003/2004 that can be related to the emerging computing paradigm of service orientation (as argued in [1]). The analysis of publications has been performed by searching for the term “Service Modeling” in the title or abstract combined. As analysis base the IEEE, Springer and ACM databases in the period from 1990 to 2011 have been selected whereas these databases also integrate and combine other sources such as IBM, IET, AIP or AVS. The statistic of publications in recent years indicate the dynamic of the topic service models, hence identified challenges require novel solution to bridge business process with technical service models. The structure of the paper is as follows: Section II discusses related work for both (a) different service viewpoints as well as (b) different service models. Section III introduces service models challenges that arise when bridging business

processes with technical service models. Section IV introduces the hybrid service model approach that is a promising candidate to solve aforementioned service model challenges. Section V introduces prototypes for conceptual and technical realization of hybrid service modeling.

II. RELATED WORK

A. Service as a Concept Modeling of services became more prominent in recent

years fostered by the requirement to better understand, define and control the services as basic building blocks of SOA-based environments. Modeling services strongly depends on specific application scenario of the deployed services relating to the deployment and management infrastructure resulting in different definitions of the service as a concept itself by the community. In [2], author speaks of six prominent examples: (1) Service as Interaction [3], (2) Service as Capability [4], (3) Service as Operation, (4) Service as Application, (5) Service as Feature, and (6) Service as Observable Behavior [5]. Having the definitions of [2] in mind we distinct in our analysis of service modeling between three groups of research work:

(1) Usage of Models: work performed in this area discusses how modeling techniques are used in different phases of a service’s lifecycle to make the complexity tangible. Four fields can be identified: (a) Service Orchestration, (b) Service Requirements Engineering, (c) Quality of Service and (d) Security Aspects in Service Environments.

(2) Definition of Modeling Approaches: work has been performed in the area of developing modeling approaches ranging from extending and enhancing existing framework (Zachmann framework supported by Ontologies), applying work on the SOA environment (UML for SOA, i* for service quality modeling in TROPOS [36]) to establishing common groundings for conceptualization of service models.

(3) Modeling Challenges have been identified for aspects such as transformation of models and semantic loss as well as introduction on different abstraction levels to make models usable by domain experts with different backgrounds. Modeling is a necessity in order to support: (a) ability to be used in different infrastructures by different actors achieving different goals and (b) some services may be created after cooperation of stakeholders from different domains (see [6]). An aspect related to Multi-Domain

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modeling targets the alignment issue between business and IT perspectives as business level cannot benefit from SOA if it stays at the software level and thus covers the high level overview from the business perspective [7].

B. Service Models Engineering of services using a model-driven approach

became a prominent field in the research and commercial world in recent years. The model-driven approach has been utilized in different domain contexts (e.g. business and administration, software engineering, etc.) in order to support and allow mastering of service life cycles. Nowadays in our world where modeling is a commodity different service models are being used to model specific parts of the service life cycle. A multitude of languages and concepts is available from research as well as industrial background, briefly introduced and analyzed in the following.

First we have models for the orchestration of services like workflow related languages such as the Business Process Execution Language (BPEL): The Web Services Business Process Execution Language [8], EPML: the Event-Driven Process Chain (EPC) Markup Language (EPML) [9], ILOG JRules: ILOG provide a Business Rules Management system [10], JessRules [11], OWL-S: The Semantic Markup for Web Services [12] (formerly DAML S), OWL-WS [13] or SAWSDL [14].

For the concept of services: RDF [15], RDF/S - RDF Schema [16], OWL [15] SWRL [17], SML [18], WS-CDL [19], WSMO [20], WSDL [21], WSCI [22], RuleML [23], WSML [24][25]. An enriched service modeling framework has been developed in the EU-Project DIP introducing a modeling framework for semantic web-services [26].

Another approach is the Model Driven Architecture (MDA) [27] that guides the software development with appropriate modeling approaches. This approach has been adapted for the service development MDD4SOA [28]. The MDD4SOA has been developed as part of the EU-Project Sensoria [29] that reflects functional and non-functional requirements of services.

Functional requirements are usually derived from business process models like XPDL - the XML Process Definition Language (XPDL) [30], IDEF3 [31], PNML - new Petri net types [32], BPSS - The Business Process Specification Schema [8], BPMS: Business Process Management Systems [33], BPMN: Business Process Modeling Notation [27], RAD: A Role Activity Diagrams (RAD) [34].

Non functional requirements can be modeled with i* [35]. An agent-based approach to model non-functional requirements is TROPOS. The issues to establish business and IT alignment is addressed in Zachman [37], TOGAF [38], or PROMET [39]. An ontological extension of the Zachmann framework [40] is introduced to relate different models via ontologies. Models for Service Level Agreements and trust are mentioned in the EU-project Assess Grid [41], COMPAS [42], or in [43].

C. Applications of Service Models Model-based approaches are used for (a) orchestrating

services, (b) model-driven development for service oriented approaches, (c) functional requirement definition, (d) non-functional requirement definition and (e) service level agreements specification. Beside this technical focus of service models there are also approaches for business entities, business intention models, business motivation models, compliances with quality standards and the like.

III. THE CHALLENGE IN SERVICE MODELS Different phases of the service lifecycle are supported by

different service models. For example service analysis phase can be supported by BPMS or EPC, service design phase by i* and UML, etc. We selected a Service Life Cycle Model and allocated existing Service Modeling Approaches from the literature although such allocation can be applied to different frameworks. The challenge is independent of the selected Service Life Cycle Model. Currently the major issues of the observed model-driven service lifecycle approaches lies in its rapid acceptation and closed view on specific phases, creating well modelled phases that are not easily compatible with each other (e.g. input for the successor phase in the lifecycle are created from different point of view, with different language and different goals). Each one of these phases constitutes an ecosystem in its own right, with its various stakeholders trying to achieve isolated results, influenced by different regulations and environmental grounding. The (modelling) languages used in each of the phases are tailored and customised to the tasks defined within and therefore produce results that are, although optimal inside any given phase, too specific in the overall lifecycle. It is exactly this focused approach that creates significant challenges when moving forward between phases in the lifecycle. Although it unarguably works and produces results – as experienced by its application in everyday work – the result creation process offers opportunities to improve in efficiency and effectiveness (for example regarding non-compatible languages without automatic translation or missing the modeling within specific phases completely). Some of the important obstacles we observed when focusing on the goal to reduce the inefficiency of the service life cycle include:

• Communication between different domains (application engineer and service engineer)

• Transformation from „informal“ to „formal“ languages

• Cover possible/available gaps in the service lifecycle (e.g. no modelling method used for a specific phase)

• Integrated domain-based views for different stakeholders in the service lifecycle chain

Hybrid Service Modeling overcomes aforementioned issues by taking results of the service modeling communities and allows a combination approach. Consequently we are not in a favor of any service life cycle hence support any given lifecycle developed (see [44], [45] or [46] or industrial driven approach such as ITIL®). The challenge to allow a combination and dynamic development of SLC for a specific

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scenario, results in the following research questions: (1) Conceptualization of specific modeling methods: how to map to / define a common abstraction level (Meta2Model) (see [47]) as a common thinking model for conceptualization of the modeling methods in the service lifecycle domain; (2) Transformation and translation between modeling languages on different levels of abstraction: having two overlapping modeling methods at hand, how is transformation and translation possible also taking into consideration how transitions between phases of the lifecycle model are handled and possible gaps are regarded in the conceptualization; (3) Integrated Views and Viewpoints in a combined environment: Having different building blocks, how can a view concept capture the inputs and provide views and perspective on a comprehensive level taking into consideration various stakeholders and domain experts.

IV. THE HYBRID MODEL APPROACH

A. Generic Modelling Method Framework When conceptualizing different service model

approaches, we need to introduce a higher abstraction that is valid for every service model. The generic modeling method framework enables the dissection of any service model approach and hence enables to start with a generic conceptualization. In order to do this one has to identify all relevant concepts of the specific modeling method used in the modeling of service lifecycles.

Figure 1 Modeling Method Framework

Figure 3 introduces the key parts that define a modeling method (see [47], [48], [49], [50] for details). They include: The modeling language itself needs to be specified. Here the Meta2Model approach can be applied in order to agree on a common definition for the modeling languages. As a candidate to build up a common understanding on a Meta2 level, ontological approaches such as the OWL notation are regarded as appropriate to specify the modeling language, so that each modeling languages describes its elements based on the Meta2Model approach using the OWL syntax. The modeling procedure is usually a text document that defines the different steps of modeling and specifies the overall aim of the model-based approach by introducing the expected modeling results. BPMN is an appropriate candidate to describe this sequence. The mechanism and algorithms are used in order to enable the model-language and model processing like: (1) the conversion from model language to ontologies and vice

versa, (2) the validation of models and the validation of modeling languages, and (3) the conversion from models to ontologies and vice versa as well as the transformation, reference, and integration of modeling languages and models. UML diagrams seem appropriate to further specify mechanisms and algorithms. All service model approaches can hence be transformed in comparable modeling methods. Such methods are used to model a specific phase of the service life cycle (here we see standards, specification frameworks etc. as modeling methods) and can be analyzed according the modeling framework depicted in Figure 1.

Identifying appropriate common reference ontologies for modeling languages, like MOF expressed in OWL, enables then syntactical comparison of service models.

Identifying common domain ontologies for the particular domain the service model is applied enabling the semantic comparison between service models. As this semantic comparison heavily depends on the domain of service model application, it is necessary to find or develop a common reference model. Notational comparison is usually not performed, as diagrammatic models typically use a limited set of graphical concepts. In case the Service Life Cycle phases are performed as a sequence, the model procedures and mechanisms and algorithms need no comparison or integration. In case several service model approaches within one Service Life Cycle phase are performed in parallel, the comparison and integration needs to be considered. Our first step in Hybrid Service Modeling is concerned with integration of modeling languages. The Open Model Initiative [48] proposes an open platform for models and modeling languages in a similar way like open source does for software in order to support the aforementioned conceptualization of service modeling approaches. There are different Open Models projects categories relevant for Hybrid Service Models; First, service providers or service consumers are invited to use the Open Model platform [51] to announce their solution or their demand in the modeling language they prefer. This involves the modeling of service requests using business process models, business models or workflow models in any standard or notation that is appropriate for the service consumer or provider. Second, service providers or service consumers are invited to implement modeling services, such as template service for SLA or service discovery services, agent-based services that observe a certain behavior or the like and to plug-in their solutions into the open model framework. This enables the usage of the model in a personalized way, as individual solutions and common models are combined for service management. The Open Service Modeling approach has been applied in the realization of the IT-Socket for business and IT alignment in the plugIT project (see [56] for details).

B. A Framework for Business and IT Alignment To accomplish alignment between business process

models and technical service models different service models have been classified (cmp. Zachmann) according to:

• Perspectives - clarifying the role of the user and the application fields of the modeling language

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• Aspects - what should be modeled dealing with the application fields and the modeling concepts

• Formalization - the level of formalization and the graphical notation, i.e. syntax, the semantics and expressiveness of the languages.

• Language families - grouping modeling languages which are based on a common philosophy.

Outcomes of the first step is a classification schema for modeling language – here represented as cubes - as shown in Figure 2. Each of the cubes can be modeled with a set of different modeling languages that are collected and maintained in form of a Modeling Language WiKi [52].

Figure 2 Modeling Language WiKi [52]

In the second step the integration of the classified modeling languages – based on the requirements imposed by a specific service lifecycle phase, has been carried out. Based on the specific requirements of the application domain (e.g. from the Enterprise Computing (EC) point of view), modeling languages classified in Figure 2, result in different configuration of the matrix. These “selections” can be influenced by e.g. skills or preferences of the stakeholders, available technical background, etc.

The integration approach used in the plugIT project which included the application of the Hybrid Modeling Approach is described in the next section.

V. REALISATION OF HYBRID MODELLING

A. Conceptual Integration with Hybrid Service Modelling The Hybrid Modeling Approach, based on meta models

allow different integration forms, as defined by [54]. In general there are three main categories for hybrid approaches: (a) loose integration patterns reference or transform different service models, (b) intermediate integration patterns use or aggregates different service models and (c) strong integration patterns merge or extend different service models. Intermediate and strong integration patterns require modeling method engineering and hence must be performed before the service model approach is actually applied by the user. Loose integration pattern can be performed while applying a service model approach and hence are more flexible. This flexibility raises challenges, which have been considered in this research work. The research question was, if modeling languages can be

orchestrated in a similar way like services are orchestrated in workflow composition. If this would be the case, then any modeling language can be potentially selected in any of the Service Life Cycle phases and would have the capabilities to be loosely integrated with previously used service model approaches. This loosely model integration has the following pre-requisites:

• Any service model can be conceptualized according the general modeling method framework.

• Any service modeling language can be realized following the meta model approaches.

• Any meta model of a service modeling language can be expressed in a so-called Modeling Language Ontology (MLO) that considers the syntax and semantic of a modeling language.

• Every model created by using a modeling language can be “semantically lifted” to annotate relevant parts of the model with a domain specific ontology (DO) that describes the context of the model.

• Every model created by using a modeling language can be syntactically expressed as model ontology (MO).

Bullet point one and two are well researched and applied, hence are taken for granted. Bullet points three, four and five need careful consideration. In the first step model ontology (MO) is derived out of existing models and model language ontology (MLO) is created based on the applied modeling language. MO and MLO are then annotated with the domain ontology (DO). Therefore it is important to find appropriate domain ontology. Pragmatic approaches initially search for domain ontologies that seem relevant for the application field, irrelevant parts are cut off and individual parts that possibly were not covered are added. Hence basic knowledge in handling ontologies is required, when applying hybrid semantic modeling. In some cases the DO is not existent and it is initially generated from the MO and then subsequently enriched. Finally the different MLO’s are mapped to the common upper ontology – the Conceptual Reference Ontology (CRO). The CRO is used to enable a common understanding between the MLO’s and allow the integration and transformation between the modeling languages. Practical approaches show that the MLO form the best known modeling language in the applied area is originally taken as the CRO. Additional MLO’s are then either mapped or the CRO is extended where necessary. The annotation of modeling languages to CRO is the semantic lifting of modeling languages. This semantic lifting, in the most extreme case, can be performed while modeling. In the simplest case, model objects are annotated by entering the URL of the CRO concept in a text field attribute. In more advanced semantic lifting, which requires method engineering, the URL to CRO concepts are specified as part of the modeling language as hidden attributes. Semantic lifting from the model by annotating a model object with DO concepts can also be performed in a trivial way, by copying the URL to DO concepts into text field attribute. More advanced techniques, which again

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require method engineering, are either (a) own text filed for the DO URL’s, (b) so-called model object references to a “transit model” that imports the DO concepts into the service modeling tool, just to enable the reference to a DO concept within one tool (hence this concept is duplicated into the service modeling tool) or (c) in case DO concepts are stable, they are implemented as enumeration fields or check boxes within the modeling language. Currently the semantic lifting of the modeling languages is performed manually, by introducing the required semantic concepts (annotations) in a specific attribute field of the modeled objects (e.g. service endpoints). Hence current approaches are very flexible but error prone and difficult to be handled by the user.

B. Technical Integration with Hybrid Service Modelling On the technical level, the hybrid service modeling has been implemented by applying the workflow and service orchestration techniques to hybrid service modeling. Hence the following pre-requisites have to be implemented: (1) every service model can be accessed as a service, (2) every service model can be expressed as an MO, (3) every service modeling language can be expressed as a MLO, (4) Every service model and very service modeling language is semantically lifted and (5) every MLO, MO and DO can be accessed as a service. In case the aforementioned pre-requisites are fulfilled, hybrid service modeling can be realized by (1) a set of modeling services that perform aforementioned tasks, (2) a set of semantic services that perform the actual task of transformation, merging, comparison or the like as well as (3) a workflow engine that orchestrates all aforementioned services to achieve the goal of hybrid service modeling. This workflow engine is named Semantic Modeling Kernel (SMK). SMK is composed of a set of services exposed as web services. The SMK services classification which is detailed in D4.1.2 [55] results in following service groups: (1) Services for Model Language Processing – provides functionality for generating and validating a Model Language Ontology (MLO) starting from a modeling language; (2) Services for Model Processing – provides functionality for generating and validating a Model Ontology (MO) starting from a model;; (3) Services for Semantic Processing – is composed of services providing a set of (generally fixed and well identified) functionalities mainly relying on semantics. They are used to match or integrate modeling languages with ontologies models; (4) Services for Domain-Specific Graphical Representation – services dealing with abstract notation languages to describe the notation of all modeling objects based on their meaning. They deal with the graphical appearance of the models. Figure 3 provides a more detailed overview of how aforementioned service groups have been used to apply the hybrid combination approach within the plugIT use cases. Starting from different graphical modeling languages, the

SMK is able to derive MLO’s and MOs through converting services, and to derive CRO’s through integration services.

Figure 3 SMK Functionality [55]

It also shows how it is possible to convert an MO (or MLO) into a different MO (MLO) or annotate an MO with a DO. A detailed description of the use cases is provided in [53].

VI. CONCLUSION AND OUTLOOK The work presented in this paper was directed toward a specific problem of mastering the modeling of services in the Service Life Cycles (SLC) in the sense of Enterprise Computing focusing on the establishment of the IT and Business alignment within the different phases of the SLC. The proposed solution to overcome the identified challenges within the diverse phases of the SLC- the Hybrid Service Modeling (HSM) approach has been presented both on the conceptual level, focusing on the integration of the SLC modeling languages, as well as on the technical level presenting briefly the development and deployment within three use cases in the plugIT project. The semantic lifting approach, one of the core elements of the HSM, has been presented on different abstraction levels, showing the method of how it was applied in the research project and identifying future research goals. In order to foster the research work on the HSM the Open Model Initiative has been selected as a platform to elevate the scientific research and real life application by making it available to interested 3rd parties in an open and accessible way.

ACKNOWLEDGMENT We would like to thank all partners of the plugIT

consortium for their ongoing support during the development of the presented research work.

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