Current technologies aimed at supporting processes – whether it is a business or learning process – primarily follow a metadata- and data-centric paradigm. Whereas process metadata is usually based on a specific standard specification – such as the Business Process Modeling Notation (BPMN) or the IMS Learning Design Standard – the allocation of resources is done manually at designtime, and the used data is often specific to one process context only. These facts limit the reusability of process models across different standards and contexts. To overcome these issues, we introduce an innovative Semantic Web Service-based framework aimed at changing the current paradigm to a context-adaptive service-oriented approach. Following the idea of layered semantic abstractions, our approach supports the development of abstract semantic process model- reusable across different contexts and standards- that enables a dynamic adaptation to specific actor needs and objectives. To illustrate the application of our framework and establish its feasibility, we describe a prototypical application in the E-Learning domain. 1.

Many applications have a need for a common terminology, to ensure that shared information will have the same meaning to everyone using it. For example, doctors need a common terminology to describe an illness; two software agents exchanging information needs to understand each other even if they use different vocabularies. An ontology is one way to represent terms and relations between terms in a structural way, which enables sharing and reuse of knowledge.

Current technologies aimed at supporting processes – whether it is a business process or a learning process – are usually based on using a dedicated set of metadata to describe a process which refers to some specific data, used in the process. Process metadata is usually specific to a standard specification – like the Business Process Modeling Notation (BPMN) or the IMS Learning Design Standard – while used process data is specific to a specific process context. These facts limit the re-usability of a process model across different standards and contexts. To overcome these issues, this paper describes an innovative semantic web service-oriented architecture aimed at changing this data- and metadata-based paradigm to a highly dynamic service-oriented approach following the idea of a semantic abstraction from process metadata as well as process data. This approach enables a dynamic adaptation to specific actor needs and semantic process models which are re-usable across different contexts and standards. To illustrate the application of our approach, we describe a prototypical application to the domain of E-Learning. 1.

Abstract. The current state of the art in supporting e-learning objectives is primarily based on providing a learner with learning content by using metadata standards. Due to this approach, several issues have to be taken into account – e. g. limited re-usability across different standards and learning contexts and high development costs. To overcome these issues, this paper describes an innovative semantic web service-oriented framework aimed at changing this data- and metadata-based paradigm to a highly dynamic service-oriented approach. Instead of providing a learner with static data, our approach is based on fulfilling learning objectives based on a dynamic supply of services. Therefore, we introduce a semantic layer architecture to abstract from existing learning data as well as process metadata standards by using Semantic Web Service (SWS) technology. Furthermore, our approach is based on abstract and reusable learning process models describing a learning process semantically as a composition of learning goals. Based on the formal semantic descriptions of learning goals as well as web services, services appropriate to achieve a specific learning goal can be selected, composed and invoked dynamically. This supports a high level of re-usability since a dynamic adaptation to different learning contexts and requirements of individual learners is achieved while utilizing standard-compliant learning applications. To illustrate the application of our approach, we describe a prototypical implementation utilizing the introduced approach based on the SWS framework WSMO.

Abstract: IMS Learning Design (IMS-LD) is a promising technology aimed at supporting learning processes. IMS-LD packages contain the learning process metadata as well as the learning resources. However, the allocation of resources- whether data or services- within the learning design is done manually at design-time on the basis of the subjective appraisals of a learning designer. Since the actual learning context is known at runtime only, IMS-LD applications cannot adapt to a specific context or learner. Therefore, the reusability is limited and high development costs have to be taken into account to support a variety of contexts. To overcome these issues, we propose a highly dynamic approach based on Semantic Web Services (SWS) technology. Our aim is moving from the current data- and metadata-based to a context-adaptive service-oriented paradigm. We introduce semantic descriptions of a learning process in terms of user objectives (learning goals) to abstract from any specific metadata standards and used learning resources. At runtime, learning goals are accomplished by automatically selecting and invoking the services that fit the actual user needs and process contexts. As a result, we obtain a dynamic adaptation to different contexts at runtime. Semantic mappings from our standard-independent process models will enable the automatic development of versatile, reusable IMS-LD applications as well as the reusability across multiple metadata standards. To illustrate our approach, we describe a prototype application based on our principles.

“The limits of my language mean the limits of my world.”

Current technologies aimed at supporting learning goals primarily follow a data and metadata-centric paradigm. They provide the learner with appropriate learning content packages containing the learning process description as well as the learning resources. Whereas process metadata is usually based on a certain standard specification – such as ADL SCORM or the IMS Learning Design – the used learning resources – data or services- are specific to pre-defined learning contexts, and they are allocated manually at design-time. Therefore, a content package cannot consider the actual learning context, since this is only known at runtime of a learning process. These facts limit the reusability of a content package across different standards and contexts. To overcome these issues, this paper proposes an innovative Semantic Web Service-based approach that changes this data- and metadata-based paradigm to a context-adaptive service-oriented approach. In this approach, the learning process is semantically described as a standard-independent process model decomposed into several learning goals. These goals are accomplished at runtime, based on the automatic allocation of the most appropriate service. As a result, we address the dynamic adaptation to specific context and- providing the appropriate mappings to established metadata standards- we enable the reuse of the defined semantic learning process model across different standards. To illustrate the application of our approach and to prove its feasibility, a prototypical application based on an initial use case scenario is proposed.

The current state of the art in supporting E-Learning objectives is primarily based on providing a learner with learning content by using metadata standards like ADL SCORM 2004 or IMS Learning Design. By following this approach, several issues can be observed – e. g. high development costs due to a limited reusability across different standards and learning contexts. To overcome these issues, our approach changes this data-centric paradigm to a highly dynamic service-oriented approach. By following this approach, learning objectives are supported based on a automatic allocation of services instead of a manual composition of learning data. Our approach is fundamentally based on current Semantic Web Service (SWS) technology and considers mappings between different learning metadata standards as well as ontological concepts for E-Learning. Since our approach is based on a dynamic selection and invocation of SWS appropriate to achieve a given learning objective within a specific learning context, it enables the dynamic adaptation to specific learning needs as well as a high level of reusability across different learning contexts.

The goal of this project is to provide the user of an e-government portal, exposed by a given public agency, with the ability to modify personal information upon occurrence of a life-event, and to alleviate the redundancy inherent to the process. A change of address for example, which must be acknowledged by several agencies, should be notified once using a portal; agencies related to this service would be informed of its occurrence and only missing or ambiguous data will be requested. To achieve this in a maintenable way the whole process should be ontology-driven (Guarino, 1998) meaning that data is mapped according to semantic specifications and that the portal is directly based on an ontology. In order to achieve ontologybased software development and to ensure interaction between the various components, additional knowledge modelling techniques presented independently in (Tanasescu et al., 2004) were introduced. Acknowledgments I would like to thank John Domingue, my supervisor at KMi, for having

2. The rational behind the development of task ontology 6 2.1 A phases in the development of task ontology 7 3. A generic specification of scheduling task 9