Context - Various research teams, as well as individual researchers, have investigated mapping modelling languages. However, systematic studies that provide a structured overview of this research on this topic have not been conducted. It is noticeable that this leaves a big gap in the context of a modelling language. Conducting these studies could lead to a better understanding of the characteristics of mapping modelling languages, which would be of great importance for the future development of this area of research. Objective - The aim of the study is to assess the state of knowledge about mapping modelling languages and assist stakeholders in making informed decisions. This is carried out by identifying existing mapping modelling languages, and their characteristics. Another objective of this thesis is to identify potential mapping modelling languages that can support the generation of a blended modelling environment. Method - In order to achieve the goal, we conducted a systematic mapping study of mapping modelling languages. Our search showed that we had 2913 potential studies that were relevant to our topic. After the selection process, the final set of primary papers was 29. The information that was of importance for this study was derived according to the categories of a well-defined classification framework. Results - The analysis of the extracted data showed the following main findings: (i) most of the primary studies research focused on providing solution proposals, (ii) the largest number of publications was in 2010, (iii) most papers mention mapping modelling languages that allow the definition of unidirectional mapping rules, (iv) the most common cardinality was 1:N, (v) graphical syntax has been proposed in many primary studies, (vi) most studies suggest mapping modelling languages that can be used to define relationships between RDF models, (vii) documentation and implementation were available for a very small number of mapping modelling languages. Conclusion - These results can help the research community to identify research gaps on mapping modelling languages as well as identify possible directions for future research.

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