A unifying structure of metamodel landscape

Abstract

Purpose

The modelling landscape experiences a rich proliferation of modelling language, or metamodel. The emergence of cross-disciplinary disciplines, such as enterprise engineering and service engineering, necessitates a multi-perspective approach to traverse the component from strategic level to technological aspect. This paper aims to find a unifying structure of metamodels introduced by academics and industries.

Design/methodology/approach

A grounded approach is taken to define the structure by collating the metamodels to form an emerging structure. Metamodels were collected from a literature survey from several interrelated disciplines: software engineering, system engineering, enterprise architecture, service engineering, business process management and financial accounting.

Findings

The result suggests seven stereotypes of metamodel, characterized by its label: goal, enterprise, business model, service, process, software and system. The aspect of “process” holds a central role in connecting all other aspect in the modelling continuum. Service engineering can be viewed as an alternative abstraction of enterprise engineering in containing the concepts of “business model”, “capability”, “value”, “interaction”, “process” and “software”.

Research limitations/implications

Metamodel collection was performed to emphasize on representativeness rather than comprehensiveness, in which old and unpopular metamodel were disregarded unless it offer unique characteristic not yet represented in the collection. Owing to its bottom-up approach, the paper is not intended to identify a gap in metamodel offering.

Originality/value

This paper produces a structure of metamodel landscape in a graphical format to illustrate correlation between metamodels in which evolutive patterns of metamodel proliferation can be observed. The produced structure can serve as map in metamodel continuum.

Citation

Yustianto, P., Doss, R. and Suhardi (2019), "A unifying structure of metamodel landscape", Journal of Modelling in Management, Vol. 14 No. 1, pp. 134-152. https://doi.org/10.1108/JM2-11-2017-0127