The meaning of a conceptual model is derived from the linguistic semantics of the modeling language used, the intension of the modeling concepts employed, and an explicit specification of these concepts that is understood within a community of practice. The triptych paradigm of conceptual modeling reflects these three dimensions of meaning as represented in the triptych wings of ‘Language Wing’, ‘Model Wing’, and ‘Meaning Wing’. In this paper, we investigate how the specification, that is, the ‘grounding’ of the modeling concepts, can be achieved based on these triptych wings. Our considerations should help the development of information systems to avoid costly future system changes that could occur due to the lack of a comprehensive understanding of an application and its inherent semantics during modeling. When developing a system, specifying the concepts used for modeling as precisely as possible increases the likelihood that the resulting information system will meet the application requirements.

This paper addresses the question of whether and how the development and use of a domain-specific modeling method (DSMM) can increase productivity in the development of technical systems in an industrial setting. This is because an essential prerequisite for DSMMs to become established in operational practice is that productivity increases can be achieved with them and qualitative benefits such as quality assurance, innovation potential, and the like can be exploited. After all, managers’ decisions are ultimately based on whether or not the use of a new method pays off. We illustrate our findings using the example of a DSMM development for the design and realization of electric vehicle testbeds, which we carried out as part of a cooperation project. This work sets the base for possible generalization into other automotive, mechatronic, and technical areas.

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.

Abstract We understand this paper as a contribution to the “anatomy” of conceptual models. We propose a signature of conceptual models for their characterization, which allows a clear distinction from other types of models. The motivation for this work arose from the observation that conceptual models are widely discussed in science and practice, especially in computer science, but that their potential is far from being exploited. We combine our proposal of a more transparent explanation of the nature of conceptual models with an approach that classifies conceptual models as a link between the dimension of linguistic terms and the encyclopedic dimension of notions. As a paradigm we use the triptych, whose central tableau represents the model dimension. The effectiveness of this explanatory approach is illustrated by a number of examples. We derive a number of open research questions that should be answered to complete the anatomy of conceptual models.

Providing reminders to elderly people in their home environment, while they perform their daily activities, is considered as a user support activity, and thus a relevant topic in Active and Assisted Living (AAL) research and development. Determining such reminders implies decision-making, since the actions' flow (behavior) usually involves probabilistic branches. An automated system needs to decide which of the next actions is the best one for the user in a given situation. Problems of this nature involve uncertainty levels that have to be dealt with. Many approaches to this problem exploit statistical data only, thus ignoring important semantic data as, for instance, are provided by Ontologies. However, ontologies do not support reasoning over uncertainty natively. In this paper, we present a probabilistic semantic model that enables reasoning over uncertainty without losing semantic information. This model will be exemplified by an extension of the Human Behavior Monitoring and Support [HBMS] approach that provides a conceptual model for representing the user's behavior and its context in her/his living environment. The performance of this approach was evaluated using real data collected from a smart home prototype equipped with sensors. The experiments provided promising results which we will discuss regarding limits and challenges to overcome.

For the presentation of Web services different kinds of readers must be considered. They have different intentions for reading a Web service. Natural language and UML seem to be adequate representation; however they have also their disadvantages. Therefore glossaries as an additional representation concept are introduced. It will be discussed to which degree glossaries can be a uniform representation format for different kinds of readers and the different information which can be derived from a Web service description.

Business process modeling is an important part of each software development project. No software is developed without specifying it's use within the context of business processes. Since business process modeling is an important task during requirements engineering, in our opinion the same basic modeling notions should be used. This paper gives a first proposal how this can be done.

Data abstractions were originally conceived as a specification tool in programming. They also appear to be useful for exploring and explaining the capabilities and shortcomings of the data definition and manipulation facilities of present-day database systems. Moreover they may lead to new approaches to the design of these facilities. In the first section the paper introduces an axiomatic method for specifying data abstractions and, on that basis, gives precise meaning to familiar notions such as data model, data type, and database schema. In a second step the various possibilities for specifying data types within a given data model are examined and illustrated. It is shown that data types prescribe the individual operations that are allowed within a database. Finally, some additions to the method are discussed which permit the formulation of interrelationships between arbitrary operations.