Abstract

Models are the key tools humans use to manage 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. However, different methods and terminologies have become established in the individual disciplines, even in the sub-fields of Informatics, which raises the need for a comprehensive and cross-sectional analysis of the past, present, and future of modeling research. This paper aims to shed some light on how different modeling disciplines emerged and what characterizes them with a discussion of the potential toward a common modeling future. It focuses on the areas of software, data, and process modeling and reports 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 the communities concerned, on a bibliometric study, and on interviews with a prominent representative of each of these communities. The paper discusses the different viewpoints of the communities, their commonalities and differences, and identifies possible starting points for further collaboration. It further discusses current challenges for the communities in general and modeling as a research topic in particular and highlights visions for the future.

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