Semantic Process Modeling – Design and Implementation of an Ontology-based Representation of Business Processes

Thomas, Oliver; Fellmann, Michael

doi:10.1007/s12599-009-0078-8

Cited by 90 publications

(47 citation statements)

References 25 publications

(15 reference statements)

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“…They can also be used to automatically analyze business processes (Becker et al 2010;Fill 2011a;Fill 2012) or as semantically enriched, machine-readable process specifications for a semantically enhanced process engine (Hepp & Roman 2007;Leutgeb et al 2007). As a consequence, different authors have proposed languages or frameworks that support adding ontological annotations to process models (Thomas et al 2009;Fill 2011b) or allow transforming a process model into a semantic business process (Hepp et al 2005;Abramowicz et al 2007;Cabral et al 2009). CMOE+, the framework described in this article, is classified as an Exaptation in the design science research knowledge contribution framework of Gregor and Hevner (2013), in the sense that known solutions are adapted to a new problem context.…”

Section: Related Workmentioning

confidence: 99%

“…In order to also support adding annotations, the MoO file imports the SemAnnO file, which defines the semantic annotation OWL object property that is used to add annotations to the OWL individuals of the MoO file. A similar approach for annotating model elements is applied by (Thomas et al 2009). This annotation approach was chosen because the rule-based recommendation service requires that the annotations are taken into account during the reasoning process.…”

Section: Ontology Storagementioning

confidence: 99%

“…This ontology is used to either suggest labels for the model elements (Delfmann 2009;Becker et al 2009b), annotate the model elements (Born et al 2007; Thomas et al 2009), or achieve a combination of both (Francescomarino et al 2011). In this case, the ontologies describe the concepts, relations and axioms that are typical of and shared within a particular enterprise; they should therefore be considered enterprise-specific ontologies (ESOs).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Recommendation-Based Conceptual Modeling and Ontology Evolution Framework (CMOE+)

Gailly¹,

Alkhaldi

Casteleyn

et al. 2017

Bus Inf Syst Eng

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Abstract. Within an enterprise, various stakeholders create different conceptual models, such as process, data, and requirements models. These models are fundamentally based on similar underlying enterprise (domain) concepts, but they differ in focus, use different modelling languages, take different viewpoints, utilize different terminology, and are used to develop different enterprise artefacts; as such, they typically lack consistency and interoperability. This issue can be solved by enterprise-specific ontologies, which serve as a reference during the conceptual model creation. Using such a shared semantic repository makes conceptual models interoperable and facilitates model integration. The challenge to accomplish this is twofold: on the one hand, an up-to-date enterprise-specific ontology needs to be created and maintained, and on the other hand, different modellers also need to be supported in their use of the enterprise-specific ontology. In this article, we propose to tackle these challenges by means of a recommendation-based conceptual modelling and an ontology evolution framework, and we focus in particular on ontology-based modelling support. To this end, we present our framework for Business Process Modelling Notation (BPMN) as a conceptual modelling language, and focus on how modellers can be assisted during the modelling process and how this impacts the semantic quality of the resulting models. Subsequently, we present a first, large-scale explorative experiment involving 140 business students to evaluate the BPMN instantiation of our framework. The experiments show promising results with regard to incurred overhead, intention of use and model interoperability.

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Section: Related Workmentioning

confidence: 99%

Section: Ontology Storagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Recommendation-Based Conceptual Modeling and Ontology Evolution Framework (CMOE+)

Gailly¹,

Alkhaldi

Casteleyn

et al. 2017

Bus Inf Syst Eng

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“…The representation of business knowledge using ontologies has become popular in recent years, with a particular focus on the representation of business processes (Thomas and Fellmann 2009;Garcia-Crespo et al 2011;Aldin and Cesare 2011;Jung et al 2015;Hachicha et al 2016). By nature, when an ontology is constructed with a focus on business processes, it lacks the information needed to shift the focus to financial aspects, which are of crucial importance in the ITBM domain.…”

Section: The Domain Of It Benchmarkingmentioning

confidence: 99%

A web-based system architecture for ontology-based data integration in the domain of IT benchmarking

Pfaff

Krcmar

2017

Enterprise Information Systems

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In the domain of IT benchmarking (ITBM), a variety of data and information are collected. Although these data serve as the basis for business analyses, no unified semantic representation of such data yet exists. Consequently, data analysis across different distributed data sets and different benchmarks is almost impossible. This paper presents a system architecture and prototypical implementation for an integrated data management of distributed databases based on a domain-specific ontology. To preserve the semantic meaning of the data, the ITBM ontology is linked to data sources and functions as the central concept for database access. Thus, additional databases can be integrated by linking them to this domain-specific ontology and are directly available for further business analyses. Moreover, the web-based system supports the process of mapping ontology concepts to external databases by introducing a semi-automatic mapping recommender and by visualizing possible mapping candidates. The system also provides a natural language interface to easily query linked databases. The expected result of this ontologybased approach of knowledge representation and data access is an increase in knowledge and data sharing in this domain, which will enhance existing business analysis methods. ARTICLE HISTORY

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“…This level of semantic accuracy is recognized as useful (or even essential) to provide the basis for the production of generalized and reusable models of organizational behavior [89]. Also, the benefits of ontology-based terminology used within the business process model include improved model distribution, integration and interoperability, and model matching [90]. Therefore, in this research, the vendor terminology (such as: SAP terms) is used and the link between the LORS forms and the vendor dictionary is established to define consistent labels for functional areas, activities, business rules, events, and other objects used to build the as-is business process.…”

Section: Workflow (Wf) Business Rules (Br) Business Rule States (Brmentioning

confidence: 99%

Process-Oriented Requirements Engineering: User-Centric LORS Framework

Al-Sabri¹,

Al‐Mashari²

2017

JSEA

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In recent years, the process orientation requirements engineering field has received significant interest. However, dealing with ordinary users within an enterprise for developing as-is business process is very complex because this requires skills, responsibility, knowledge, and expertise of business processes. This research answers the following questions: 1) how to systematically gather information regarding as-is business process requirements in an informal environment and by non-expert users? and 2) how can an enterprise refine the identified business process with a semantic process model? The primary purpose of this research is to develop a supporting framework that is suitable for the definition of an as-is business process to be deployed within the enterprise environment. Hence, the focus is on gathering requirements to define the as-is business process. This framework concentrates on three significant aspects of this process: development, refinement, and serialization the semantics of the process model. To accomplish this objective, the LORS framework has been proposed, which consists of four phases (List, Order, Refinement, and Serialization). The framework presents a new unique technique to identify the business process, refine the process, and generate the model semantics. This study assumes that a simple and complete framework will help non-expert users define a high-quality as-is process, such that enhance and facilitate the matching process with existing reference models. We present a case study, evaluate the case study relative to specified criteria, and research the limitations and implications discovered from our research. This research concludes that the LORS framework is simple, flexible, visible, interactive, dynamic, and effective.

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Semantic Process Modeling – Design and Implementation of an Ontology-based Representation of Business Processes

Cited by 90 publications

References 25 publications

Recommendation-Based Conceptual Modeling and Ontology Evolution Framework (CMOE+)

Recommendation-Based Conceptual Modeling and Ontology Evolution Framework (CMOE+)

A web-based system architecture for ontology-based data integration in the domain of IT benchmarking

Process-Oriented Requirements Engineering: User-Centric LORS Framework

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