The business process modelling ontology

In this paper we describe the Business Process Modelling Ontology (BPMO), which is part of an approach to modelling business processes at the semantic level, integrating knowledge about the organisational context, workflow activities and Semantic Web Services. We harness knowledge representation and reasoning techniques so that business process workflows can: be exposed and shared through semantic descriptions; refer to semantically annotated data and services; incorporate heterogeneous data though semantic mappings; and be queried using a reasoner or inference engine. In this paper we describe our approach and evaluate BPMO through a use case

Implementation of Aspect-oriented Business Process Models with Web Services

In software development, crosscutting concerns, such as security, audit, access control, authentication, logging, persistence, transaction, error handling etc. can be modularized using the aspect-oriented paradigm. In busi- ness process modeling, aspects have been used to reduce visualization complexity, increase reuse and improve model maintainability. There are techniques which address aspects in modeling and implementation phases of business process; however, these techniques adopt different semantic representations, hindering the integration of these phases into the BPM lifecycle. This work proposes an architecture for service discovery capable of selecting web services that implement crosscutting concerns and meet the goals established in the aspect modeling phase, executing them accordingly with a prioritization. A proof of concept to analyze the proposed architecture and generated artifacts was performed. Afterwards, the proposal was evaluated by means of an experiment. The results suggest that the def- inition of an operational goal enables the business spe- cialists to concentrate on the modeling of the aspect without necessarily concerning its implementation, since a proper option for implementation is discovered during the execution of the process

Towards an ontology for process monitoring and mining

Business Process Analysis (BPA) aims at monitoring, diagnosing, simulating and mining enacted processes in order to support the analysis and enhancement of process models. An effective BPA solution must provide the means for analysing existing e-businesses at three levels of abstraction: the Business Level, the Process Level and the IT Level. BPA requires semantic information that spans these layers of abstraction and which should be easily retrieved from audit trails. To cater for this, we describe the Process Mining Ontology and the Events Ontology which aim to support the analysis of enacted processes at different levels of abstraction spanning from fine grain technical details to coarse grain aspects at the Business Level

Methods for Efficient and Accurate Discovery of Services

With an increasing number of services developed and offered in an enterprise setting or the Web, users can hardly verify their requirements manually in order to find appropriate services. In this thesis, we develop a method to discover semantically described services. We exploit comprehensive service and request descriptions such that a wide variety of use cases can be supported. In our discovery method, we compute the matchmaking decision by employing an efficient model checking technique

ACTAS: Adaptive Composition and Trading with Agents for Services

Mainly in business domains, the vision of gaining flexible, adaptive service environments is based on the standardization and practical proliferation of (Semantic) Web Services, ontologies, and agents. The standards of Web Services and their Service-oriented Architectures (SOA) became the standard paradigm for software component integration. Dynamic changes and the permanently increasing amount of available e-services of different domains are a challenge of Service Discovery and Composition. Mediation between different approaches and expert knowledge is often necessary for the composition of services of different domains. Semantic enhancements, Autonomic Service Discovery, and the research for more holistic concepts for the classification of e-services are current attempts of overcoming this challenge, in order to reach the ultimate goal of Autonomic SOC