Conceptual Modelling: Knowledge in and about models
As the paradigm of Enterprise modeling originally envisioned, a hybridization of modeling approaches is needed in order to cover the multiple facets of a business view, its context and requirements for different types of resources - including IT services and infrastructure. The “modeling method framework” establishes key building blocks - i.e. the modeling language, the modeling procedure and mechanisms/algorithms - to enable the required hybrid modeling and to increase the value of models beyond their traditional functions. As the importance of Next Generation Enterprise Modeling in the age of the Internet of Things, Industry 4.0, Industrial 3-D printing etc.,increases, new modeling capabilities, semantically enriched design concepts and adapted operational functionality must satisfy evolving needs, in order to successfully manage not only the transformation in the digital Enterprise stage, but also the adaptation and extension of existing services.In this context, the foundations of a conceptual-model-awareness approach for next generation Enterprise Information Systems will be presented. This novel approach makes use of semantic networks to extend model-awareness towards arbitrary types of models that are developed for specialized communities aiming for domain-specificity (or even case-specificity) in their modeling language, therefore favoring productivity at the expense of reusability across domains. The technological space for capturing and bridging knowledge through model semantics is primarily based on diagrammatic models. Two categories of models are employed in this context: (1) Models of Concepts for describing a common understanding of a domain through its concepts and relations; (2) Models that use Concepts typically domain-specific models based on some already established understanding of the domain. The hereby introduced life cycle of Agile Modeling Method Engineering -AMME- aims to apply the principle of agility established in Software Engineering (e.g., evolutionary development, flexible response to change) to the practice of Modeling Method Engineering. The main assumption is that a modeling method may evolve iteratively based on changing modeling requirements and > feedback loops. Within the context of AMME, a full methodological approach is established by the OMiLab Laboratory (http://www.omilab.org), with the life cycle encompassing five phases: (1) create, (2) design, (3) formalize, (4), develop and (5) deploy/validate. The approach is supported, in its fast prototyping stage, by the meta modeling domain-specific language MM-DSL and the meta-modeling platform ADOxx (http://www.adoxx.org).
Lecture at NEMO2015
Date/Time: Monday, July 20, 2015 at 14:00