On Domain Conceptualization

The Knowledge Engineering Review, 2009

Modelling is one of the most frequent tasks in the area of information systems (ISs), with models such as schemata, ontologies, patterns and architectures forming the bases for their creation. Very often, however, the difference between these types of models is not clear and causes confusion and erratic use of the terms. The aim of this paper is to clarify the concept of model through a study of some of the more common ones used in ISs. This proposal is presented through an ontology, where we show how we conceptualize models according to their role in the development of an IS: the model understood as the representation of a domain or as a reality serving as an example.

When modelling enterprises, for instance as part of an enterprise (re)engineering effort, one typically uses a range of models. These models differ in their intended purpose in terms of the domain which the model should pertain to and the intended usage of the model by its audience. The models are therefore generally created in purpose-specific modelling languages; i.e. not just domain-specific languages. While using purpose-specific modelling languages has clear benefits in terms of the suitability of the language to a purpose at hand, there is also a downside to it. As each of the resulting enterprise models refers to (different aspects of) the same (version of the) enterprise, it is desirable to maintain coherence across the different models. The use of a wide range of purpose-specific models (and modelling languages) can easily lead to a fragmentation of the modelling landscape; i.e. a break up of coherence. This leads to a natural polarity between coherence and purpose-specificity. We argue that this polarity requires careful management, but first and foremost a better understanding. To cope with, or avoid, the consequences of fragmentation, different strategies to achieve the integration of models and languages used in enterprise modelling have been suggested in the literature. These approaches, however, focus mainly on syntactic aspects of the models, while sometimes indeed including their (for-mal) semantics, and only to some extent their pragmatics. The aim of the research, reported on in this paper, is to achieve a deeper understanding of the needs and challenges of the use of different models in enterprise modelling.

Springer eBooks, 1995

We present a logical framework for representing activities, states, and time in an enterprise model. We define an ontology for these concepts in first-order logic and consider the problems of temporal projection and reasoning about the occurrence of actions.

2021

In the context of enterprise and information systems engineering (including enterprise architecture, business process management, etc), a wide range of domain models are produced and used. Examples of such domain models include business process models, enterprise architecture models, information models, all sorts of reference models, and indeed value models and business ontologies. The creation, administration, and use, of such domain models requires an investment in terms of resources (time, money, cognitive effort, etc). We contend that such investments should be met by a (potential) return. In other words, the resulting models and / or the processes involved in their creation, administration, and use, should add value that make these investments worth while. In the work reported on in this paper, we aim to gain a better understanding of the factors that can be used to define the value of modeling. We also look forward to raising a broader discussion on this important topic at VMB...

An account is given of the possibilities and limitations of reusing Enterprise Models (EM) 1 . Special difficulties are discussed which arise from the fact that stake-holders in the enterprise engineering process do not belong to a single homogeneous language community. Measures are proposed which ensure that models are interpreted as intended, thereby controlling the quality of the processes using enterprise models -such as enterprise engineering. A practical definition of model completeness is presented, based on a pragmatic theory of meaning and theory of communication.

In the context of enterprise and information systems engineering (in-cluding enterprise architecture, business process management, etc), a wide range of domain models are produced and used. Examples of such domain models include business process models, enterprise architecture models, information models , all sorts of reference models, and indeed value models and business ontolo-gies. The creation, administration, and use, of such domain models requires an investment in terms of resources (time, money, cognitive effort, etc). We contend that such investments should be met by a (potential) return. In other words, the resulting models and / or the processes involved in their creation, administration, and use, should add value that make these investments worth while. In the work reported on in this paper, we aim to gain a better understanding of the factors that can be used to define the value of modeling. We also look forward to raising a broader discussion on this important topic at VMBO 2021.

Data & Knowledge Engineering, 2010

Business analysts, business architects, and solution consultants use a variety of practices and methods in their quest to understand business. The resulting work products often end up being transitioned into the formal world of software requirement definitions or as recommendations for all kinds of business activities. We describe an empirical study about the nature of these methods, diagrams, and home grown conceptual models as reflected in real practice at IBM. We identify the models as artifacts of "enterprise conceptual modeling". We study important features of these models, suggest practical classifications and characterizations, and distinguish them from drawings. Specifically we look into context, type, methods and complexity to determine enterprise conceptual models usage. Our survey shows that the "enterprise conceptual modeling" arena presents a variety of descriptive models, each used by a relatively small group of colleagues. Together they form a spectrum that extends from "drawings" on one end to "standards" on the other. j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / d a ta k -What types of methods/guidance do practitioners use to support their conceptual models? -How can business stakeholders distinguish drawings from conceptual models?

Computing Letters, 2005

Abstract: This position paper focuses on business domain modeling as part of requirements engineering in software development projects. Domain modeling concerns obtaining and modeling the language (concepts, terminologies; ontologies) used by stakeholders to talk about a domain. Achieving conceptual clarity and consensus among stakeholders is an important yet often neglected part of requirements engineering. Domain modeling can play a key role in supporting it. This does, however, require a nuanced approach aspects of ...

Representing organizational reality in conceptual models is an important part of IS practice. In this paper we expose and challenge the taken-for-granted ontological and epistemological assumptions that underpin common accounts of conceptual modeling, using process modeling as an example. We argue that, due to an implicit commitment to a dualist ontology and representationalist epistemology, much literature regards the elicitation and representation of reality in the course of modeling as largely unproblematic. We draw on Martin Heidegger's holistic philosophy to give an alternative analysis that brings to the fore challenges in 1) eliciting knowledge of routine activities, 2) capturing knowledge from domain experts and 3) representing organizational reality in authentic ways. As a result we come to see modeling as a practice that performs particular realities rather than simply representing a given reality. We hope to initiate a critical discussion on the implications of the current philosophical grounding of conceptual modeling.

Conceptual modelling deals with the process of building or interpreting a conceptual model. Stakeholders use the resulting model to reason and communicate about a domain in order to improve their common understanding of it. From this perspective, conceptual modelling and conceptual models are subjects for information systems research. In this paper, we argue that this engineering-driven view on conceptual models is only one possible perspective for information systems research. Based on language critique, we show how conceptual models can be used not as a subject of but as an important and useful instrument for information systems research. Conceptual models help to structure and formalize the interpretation of a subjective understanding in a domain of focus. We propose a research approach which is based on three roles that the researcher adopts and show how conceptual models are a useful source of knowledge and an instrument for interpretation respectively. We combine our view with an existing framework for information systems research and reinterpret existing research as matching to our approach.