A Metamodeling Approach to Teaching Conceptual Modeling at Large

In the authors\u27 university there is a challenge, with respect to Conceptual Modeling topics, of bridging the gap between bachelor-level studies and research work. At bachelor-level, Conceptual Modeling is subordinated to Software Engineering topics consequently making extensive use of software design standards. However, at doctoral level or in project-based work, modeling methods must be scientifically framed within wider-scoped paradigms - Design Science, Enterprise Modeling etc. In order to bridge this gap, we developed a teaching artifact to present Conceptual Modeling as a standalone discipline that can produce its own artifacts, driven by requirements in a variety of domains. The teaching artifact is an agile modeling method that is iteratively implemented by students. The key takeaway revelation for students is that a modeling language is a knowledge schema that can be tailored and migrated for specific purposes just like a database schema, to accommodate an application domain and its modeling requirements

Supporting Customized Design Thinking Using a Metamodel-based Approach

Traditional design methods, based on analytical rationale, often cannot address upcoming challenges e.g., related to the digital business transformation in volatile environments. Analytical rationale assumes a particular result and provides the methods and tools for achieving it. Nowadays, however, the result of a business transformation is often not precisely known nor the ways and means to achieve it. As a result, methods and tools are required that foster creativity while allowing customization to specific requirements or stakeholder needs. This paper proposes customized design thinking processes, realized with a conceptual modelling approach. The approach supports creativity in transformative business design. It shows how numerous design thinking tools can be integrated into a single conceptual modelling approach - supported by a modelling platform. The platform facilitates efficient and flexible design of novel business solutions. The created models moreover serve as a formalized knowledge base that enables knowledge processing and reuse

HOW CAN DIAGRAMMATIC CONCEPTUAL MODELLING SUPPORT KNOWLEDGE MANAGEMENT?

Traditionally, venues that are publishing Knowledge Management research have been separating concerns between two viewpoints that rarely converge into holistic approaches: one is the tradition of Artificial Intelligence research, where Knowledge Management is often employed as an umbrella term in relation to a variety of semantic technologies, knowledge representation and knowledge discovery techniques; the other viewpoint is a specialisation of intangible asset management , dealing with the business value and the pragmatics of organisational knowledge. Knowledge Management Systems are a catalyst for bridging such complementary perspectives and Design Science artefacts must be employed to facilitate alignments between these viewpoints, specifically between humanoriented and machine-oriented knowledge representations. Motivated by this desideratum and driven by project-based experience, the paper at hand advocates a key role of Diagrammatic Conceptual Modelling methods in enriching the seminal SECI Knowledge Conversion spiral, to the aim of opening it towards Knowledge Management Systems that could not have been envisioned at the time of Nonaka\u27s original SECI proposal, but can now benefit from state-of-the-art semantics-driven practices. By hybridising the SECI model with a machine-oriented Knowledge Distilling cycle, an extended SECI spiral variant is proposed and analysed in the paper, as a reflection on project-based deployments and experience