This position paper introduces a Smart Innovation Environment for experimentation related to digital transformation projects, for the consolidation of a proposed “Digital Engineer” skill profile (with a business-oriented facet labelled as “Digital Innovator”). In the Internet of Things era, this profile implies the ability to perform both digital design and engineering activities, to semantically bridge multiple layers of abstraction and specificity – from business analysis down to cyber-physical engineering. In the paper’s proposal, this integration is enabled by conceptual modelling methods and interoperable modelling tools, tailored to support the creation of Digital Twins for innovative digital business models. The architecture of the proposed environment is guided by a Design Research perspective – i.e., it is a treatment to an education “design problem” regarding the Digital Engineer skill profile in the IoT era. The proposed environment encompasses workspaces and toolkits are currently evaluated in “innovation corners” deployed across the OMiLAB ecosystem.

OMiLAB: A Smart Innovation Environment for Digital Engineers

This article frames Conceptual Modeling education as a design problem, in the sense of the Design Science research framework, motivated by student preconceptions and oversimplifications causing a gap between how the discipline is perceived at the bachelor level and the holistic understanding of model value that is required for research work. The treatment to this design problem must comprise teaching approaches and artifacts capable of positioning Conceptual Modeling as a standalone discipline having a value proposition for any application domain, rather than a technique subordinated to other disciplines. The underpinning thesis is that modeling languages should be primarily understood as purposeful knowledge schemas that can be subjected to agile adaptations in support of model-driven systems or knowledge processes, by analogy to how a database schema is evolved in response to changing requirements of a data-driven system or data analytics needs. This thesis is supported by enablers provided by the Open Models Laboratory and the Agile Modeling Method Engineering framework – resources that support the development of treatments to the design problem framed by the article.

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Conceptual Modeling Education as a “Design Problem”

Models evolved from mere pictures supporting human understanding to sophisticated knowledge structures processable by machines. This entails an inevitable need for computer-understandable models and languages and causes formalization to be a crucial part in the lifecycle of a modeling method. An appropriate formalism must be a means for providing a unique, unambiguous but implementation-independent way of specifying arbitrary modeling languages and for this purpose must be generic and open to capture any domain and any functionality. In this paper we give a pervasive description of the formalism MetaMorph based on predicate logic – an approach fulfilling these requirements. This is done with an extensive proof-of-concept case illustrating the application of the formalism concept by concept. For the case study we use the modeling language ProVis from the domain of stochastic education. The language ProVis comprises only few objects and relation types but with high interconnection and therefore appears as a interesting specimen for formalization and showing the feasibility of the demonstrated approach.

Formalizing Conceptual Modeling Methods with MetaMorph.

The OMiLAB Digital Innovation environment: Agile conceptual models to bridge business value with Digital and Physical Twins for Product-Service Systems development

Enterprise modeling deals with the increasing complexity of processes and systems by operationalizing model content and by linking complementary models and languages, thus amplifying the model-value beyond mere comprehensible pictures. To enable this amplification and turn models into computer-processable structures a comprehensive formalization is needed. In this paper we build on the widely accepted approach of logic as basis for modeling languages and define them as languages in the sense of typed predicate logic comprising a signature $\varSigma $ and a set of constraints. We concretize how the basic concepts of a language – object and relation types, attributes, inheritance and constraints – can be expressed in logical terms. This naturally leads to the denotation of a model as $\varSigma $-structure satisfying all constraints. We apply this definition also on the metalevel and propose a formal modeling language to specify metamodels called M2FOL. A thus formalized metamodel then rigorously defines the signature of a language and we provide an algorithmic derivation of the formal modeling language from the metamodel. The effectiveness of our approach is demonstrated by formalizing the Petri Net modeling language, a method frequently used for analysis and simulation in enterprise modeling.

M2FOL: A Formal Modeling Language for Metamodels

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Conceptual Modelling in Education: a Position Paper.

Enterprise modeling deals with the increasing complexity of processes and systems by operationalizing model content and by linking complementary models and languages, thus amplifying the model-value beyond mere comprehensible pictures. To enable this amplification and turn models into computer-processable structures a comprehensive formalization is needed. This paper presents a generic formalism based on typed first-order logic and provides a perspective on the potential and benefits arising for a variety of research issues in conceptual modeling. We define modeling languages as formal languages with a signature $\Sigma$ - comprising object types, relation types, and attributes through types and function symbols - and a set of constraints. Three cases studies are included to show the effectiveness of the approach. Applying the formalism to the next level in the hierarchy of models we create M2FOL, a formal modeling language for metamodels. We show that M2FOL is self-describing and therefore complete the formalization of the full four-layer metamodeling stack. On the basis of our generic formalism applicable to arbitrary modeling languages we examine three current research topics - language interleaving & consistency, operations on models, and automatic translation of formalizations to platform-specific code - and how to approach them with the proposed formalism. This shows that the rich knowledge stack on formal languages in logic offers new tools for old problems. 

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Victoria Döller

Papers

Conceptual Modeling Education as a “Design Problem”

Formalizing Conceptual Modeling Methods with MetaMorph.

M2FOL: A Formal Modeling Language for Metamodels

Conceptual Modelling in Education: a Position Paper.

Formalizing the four-layer metamodeling stack with MetaMorph: potential and benefits