Models are humans’ key instruments for managing complexity in description, development, and analysis. This applies to all scientific and engineering disciplines, and in particular to the development of software and data-intensive systems. Many methods and terminologies have become established leading to an increased need for a comprehensive and cross-sectional analysis of the past, present, and future of modeling research. The paper presented here was published in SoSyM and aims to shed light on how different modeling disciplines emerged and what characterizes them. We focus on software, data, and process modeling and report on an analysis of the research approaches, goals, and visions pursued in each, as well as the methods used. This analysis is based on the results of a survey conducted in these communities, on a bibliometric study, and on interviews with a prominent representative of each of these communities. In addition, we identify starting points for further collaboration.