On the General Ontological Foundations of Conceptual Modeling

Guizzardi, Giancarlo; Herre, Heinrich; Wagner, Gerd

doi:10.1007/3-540-45816-6_15

Cited by 91 publications

(73 citation statements)

References 6 publications

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“…Among other theories that have been proposed as a basis for representational analysis of conceptual modeling in information systems, the approaches of Chisholm [12] and Guizzardi et al [13] are to be regarded as closest to the ideas of Wand and Weber. These upper-level ontologies have been built for similar purposes and seem to be equally expressive [14] but have not yet achieved the popularity and dissemination of the BWW models.…”

Section: Representation Theory In Information Systemsmentioning

confidence: 99%

A Study of the Evolution of the Representational Capabilities of Process Modeling Grammars

Rosemann

Recker

Indulska

et al. 2006

Notes on Numerical Fluid Mechanics and Multidisciplinary Design

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Abstract.A plethora of process modeling techniques has been proposed over the years. One way of evaluating and comparing the scope and completeness of techniques is by way of representational analysis. The purpose of this paper is to examine how process modeling techniques have developed over the last four decades. The basis of the comparison is the Bunge-Wand-Weber representation model, a benchmark used for the analysis of grammars that purport to model the real world and the interactions within it. This paper presents a comparison of representational analyses of several popular process modeling techniques and has two main outcomes. First, it provides insights, within the boundaries of a representational analysis, into the extent to which process modeling techniques have developed over time. Second, the findings also indicate areas in which the underlying theory seems to be over-engineered or lacking in specialization.

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Section: Representation Theory In Information Systemsmentioning

confidence: 99%

A Study of the Evolution of the Representational Capabilities of Process Modeling Grammars

Rosemann

Recker

Indulska

et al. 2006

Notes on Numerical Fluid Mechanics and Multidisciplinary Design

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“…In order to tackle this ill-favored effect of complexity, we agree with (Guizzardi & Halpin, 2008) that research in ontology-driven conceptual modeling on the one hand needs to provide theoretically sound conceptual tools with precisely defined semantics but on the other hand must hide as much as possible the complexity that arise of these ontological theories. It is on this aspect that ontological rules or modeling guidelines seem promising, since it is their aim to support the conceptual modeling process to arrive at clearer, more effective and more understandable models.…”

Section: Research Opportunitymentioning

confidence: 76%

“…For instance ontological theories, such as those of Heller & Herre (2004), Chisholm (1996) and Bunge (1977), have been successfully used for the evaluation of conceptual modeling languages or frameworks (e.g. UML, ORM, ER, REA, OWL) (Guizzardi & Halpin, 2008). The usage of ontologies goes further than only evaluating conceptual modeling, in the sense that an ontology would express the fundamental elements of a domain, and therefore becoming the theoretical foundations of a conceptual model (Guarino, 1998).…”

Section: Introductionmentioning

confidence: 99%

“…Since ODCM is still a relatively new research domain in the field of information systems, there is still much discussion on how the research in ODCM should be performed and what the focus of this research should be (Guizzardi & Halpin, 2008;Saghafi & Wand, 2014). Therefore, this article aims to critically survey the existing literature in order to assess the kind of research that has been performed over the years, analyze the nature of the research contributions and establish its current state of the art by positioning, evaluating and interpreting relevant research to date that is related to ODCM.…”

Section: Introductionmentioning

confidence: 99%

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Ontology-driven conceptual modeling: A systematic literature mapping and review

Verdonck

Gailly

Cesare

et al. 2015

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Abstract. Ontology-driven conceptual modeling (ODCM) is still a relatively new research domain in the field of information systems and there is still much discussion on how the research in ODCM should be performed and what the focus of this research should be. Therefore, this article aims to critically survey the existing literature in order to assess the kind of research that has been performed over the years, analyze the nature of the research contributions and establish its current state of the art by positioning, evaluating and interpreting relevant research to date that is related to ODCM. To understand and identify any gaps and research opportunities, our literature study is composed of both a systematic mapping study and a systematic review study. The mapping study aims at structuring and classifying the area that is being investigated in order to give a general overview of the research that has been performed in the field. A review study on the other hand is a more thorough and rigorous inquiry and provides recommendations based on the strength of the found evidence. Our results indicate that there are several research gaps that should be addressed and we further composed several research opportunities that are possible areas for future research. IntroductionConceptual models were introduced to increase understanding and communication of a system or domain among stakeholders. According to Stachowiak (1973), a conceptual model possesses three features: (1) a mapping feature, meaning that a model can be seen as a representation of the 'original' system, which is expressed through a modeling language; (2) a reduction feature, characterizing the model as only a subset of the original system and (3) the pragmatics of a model which describes its intended purpose or objective.Conceptual modeling is the activity of representing aspects of the physical and social world for the purpose of communication, learning and problem solving among human users (Mylopoulos, 1992). Conceptual modeling has gained much attention especially in the field of information systems, for design, analysis and development purposes. Their importance was understood in the 1960s, since they facilitate detection and correction of system development errors (Wand & Weber, 2002). The higher the quality of conceptual models, the earlier the 2 detection and correction of these errors occurs. This increase in attention and importance attributed to conceptual modeling led to the development and introduction of a wide range of various conceptual modeling approaches and techniques. Criticism however arose, stating that these approaches and techniques still lacked a comprehensive and generally acknowledged understanding (Moody, 2005). In addition, many conceptual models lacked an adequate specification of the semantics of the terminology of the underlying models, which led to inconsistent interpretations and uses of knowledge (Grüninger, Atefi, & Fox, 2000). In order to provide a foundation for conceptual modeling, ontologies were introduced. As mentio...

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“…How to reconcile these two sets of contradicting requirements? As advocated by [7], actually two classes of languages are required to fulfill these two sets of requirements. Moreover, as any other engineering process, an ontology engineering process lifecycle should comprise phases of conceptual modeling, design, and implementation.…”

Section: Introductionmentioning

confidence: 99%

On the Importance of Truly Ontological Distinctions for Ontology Representation Languages: An Industrial Case Study in the Domain of Oil and Gas

Guizzardi

Lopes

Baião

et al. 2009

Enterprise, Business-Process and Information Systems Modeling

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Abstract. Ontologies are commonly used in computer science either as a reference model to support semantic interoperability, or as an artifact that should be efficiently represented to support tractable automated reasoning. This duality poses a tradeoff between expressivity and computational tractability that should be addressed in different phases of an ontology engineering process. The inadequate choice of a modeling language, disregarding the goal of each ontology engineering phase, can lead to serious problems in the deployment of the resulting model. This article discusses these issues by making use of an industrial case study in the domain of Oil and Gas. We make explicit the differences between two different representations in this domain, and highlight a number of concepts and ideas that were implicit in an original OWL-DL model and that became explicit by applying the methodological directives underlying an ontologically well-founded modeling language.

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On the General Ontological Foundations of Conceptual Modeling

Cited by 91 publications

References 6 publications

A Study of the Evolution of the Representational Capabilities of Process Modeling Grammars

A Study of the Evolution of the Representational Capabilities of Process Modeling Grammars

Ontology-driven conceptual modeling: A systematic literature mapping and review

On the Importance of Truly Ontological Distinctions for Ontology Representation Languages: An Industrial Case Study in the Domain of Oil and Gas

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