TemporalEMF: A Temporal Metamodeling Framework

Abstract

Existing modeling tools provide direct access to the most current version of a model but very limited support to inspect the model state in the past. This typically requires looking for a model version (usually stored in some kind of external versioning system like Git) roughly corresponding to the desired period and using it to manually retrieve the required data. This approximate answer is not enough in scenarios that require a more precise and immediate response to temporal queries like complex collaborative co-engineering processes or runtime models.

In this paper, we reuse well-known concepts from temporal languages to propose a temporal metamodeling framework, called TemporalEMF, that adds native temporal support for models. In our framework, models are automatically treated as temporal models and can be subjected to temporal queries to retrieve the model contents at different points in time. We have built our framework on top of the Eclipse Modeling Framework (EMF). Behind the scenes, the history of a model is transparently stored in a NoSQL database. We evaluate the resulting TemporalEMF framework with an Industry 4.0 case study about a production system simulator. The results show good scalability for storing and accessing temporal models without requiring changes to the syntax and semantics of the simulator.

This work was supported by the Austrian Federal Ministry for Digital, Business and Enterprise and by the National Foundation for Research, Technology and Development; the Programa Estatal de I+D+i Orientada a los Retos de la Sociedad Spanish program (Ref. TIN2016-75944-R); and the Electronic Component Systems for European Leadership Joint Undertaking under grant agreement No. 737494. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and from Sweden, France, Spain, Italy, Finland & Czech Republic.