Effects of Domain Familiarity on Conceptual Modeling Performance

2017 ◽  
Vol 28 (2) ◽  
pp. 27-55 ◽  
Author(s):  
Jihae Suh ◽  
Jinsoo Park
Keyword(s):  
Information Systems ◽  
Conceptual Model ◽  
Conceptual Models ◽  
Conceptual Modeling ◽  
Experimental Methodology ◽  
Information Systems Development ◽  
Theoretical Contribution ◽  
Semantics And Pragmatics ◽  
Domain Familiarity ◽  
User Knowledge

Conceptual modeling is currently considered a significant phase in information systems development. Several modeling grammars and methods have been studied extensively in the information systems discipline. However, previous research on conceptual models has focused on certain grammar (syntax) or discovering a way to deliver the meaning of a model (semantic) more clearly and completely. With regard to the construct overload issue in conceptual modeling, past studies have had some deficiencies in research methods and even presented contradicting results. The objective of the present study is twofold. First, the authors researched the interaction effect among syntax, semantics, and pragmatics to discover the preferred design, context, and user knowledge with which models are more likely to be understood or interpreted. Second, they performed an experiment to reconcile conflicting outcomes and acquire a more complete and accurate understanding of construct overload. Specifically, the authors focused on understanding the end users' modeling performance between ontologically clear and unclear models. They applied an improved experimental methodology that integrates three features (i.e., syntax, semantic, pragmatic) rather than treat them individually and employs different degrees of domain familiarity in the conceptual model (i.e., familiar domain vs. unfamiliar domain). The result of this study will broaden the perspective on usability in the context of the conceptual model and may serve as a modeler's ontological guidance in terms of whether or not to contain construct overload when they create a model. In addition, this study makes the theoretical contribution by verifying the domain extensibility towards the theory of ontological clarity.

Using Ontology Languages for Conceptual Modeling

2012 ◽  
pp. 1-28
Author(s):  
Palash Bera ◽  
Anna Krasnoperova ◽  
Yair Wand
Keyword(s):  
Conceptual Models ◽  
Conceptual Modeling ◽  
Systems Development ◽  
Information Systems Development ◽  
Semantic Relationships ◽  
Support Domain ◽  
Domain Semantics ◽  
Ontology Languages ◽  
Conceptual Modeling Grammar ◽  
Precise Representation

Conceptual models are used to support understanding of and communication about application domains in information systems development. Such models are created using modeling grammars (usually employing graphic representation). To be effective, a grammar should support precise representation of domain concepts and their relationships. Ontology languages such as OWL emerged to define terminologies to support information sharing on the Web. These languages have features that enable representation of semantic relationships among domain concepts and of domain rules, not readily possible with extant conceptual modeling techniques. However, the emphasis in ontology languages has been on formalization and being computer-readable, not on how they can be used to convey domain semantics. Hence, it is unclear how they can be used as conceptual modeling grammars. We suggest using philosophically based ontological principles to guide the use of OWL as a conceptual modeling grammar. The paper presents specific guidelines for creating conceptual models in OWL and demonstrates, via example, the application of the guidelines to creating representations of domain phenomena. To test the effectiveness of the guidelines we conducted an empirical study comparing how well diagrams created with the guidelines support domain understanding in comparison to diagrams created without the guidelines. The results indicate that diagrams created with the guidelines led to better domain understanding of participants.

Using Ontology Languages for Conceptual Modeling

2010 ◽  
Vol 21 (1) ◽  
pp. 1-28 ◽  
Author(s):  
Palash Bera ◽  
Anna Krasnoperova ◽  
Yair Wand
Keyword(s):  
Conceptual Models ◽  
Conceptual Modeling ◽  
Information Systems Development ◽  
Semantic Relationships ◽  
Modeling Techniques ◽  
Support Domain ◽  
Domain Semantics ◽  
Ontology Languages ◽  
Conceptual Modeling Grammar ◽  
Precise Representation

Conceptual models are used to support understanding of and communication about application domains in information systems development. Such models are created using modeling grammars (usually employing graphic representation). To be effective, a grammar should support precise representation of domain concepts and their relationships. Ontology languages such as OWL emerged to define terminologies to support information sharing on the Web. These languages have features that enable representation of semantic relationships among domain concepts and of domain rules, not readily possible with extant conceptual modeling techniques. However, the emphasis in ontology languages has been on formalization and being computer-readable, not on how they can be used to convey domain semantics. Hence, it is unclear how they can be used as conceptual modeling grammars. We suggest using philosophically based ontological principles to guide the use of OWL as a conceptual modeling grammar. The paper presents specific guidelines for creating conceptual models in OWL and demonstrates, via example, the application of the guidelines to creating representations of domain phenomena. To test the effectiveness of the guidelines we conducted an empirical study comparing how well diagrams created with the guidelines support domain understanding in comparison to diagrams created without the guidelines. The results indicate that diagrams created with the guidelines led to better domain understanding of participants.

Modeling Approach for Integration and Evolution of Information System Conceptualizations

2013 ◽  
pp. 146-175
Author(s):  
Remigijus Gustas
Keyword(s):  
Information System ◽  
Information Systems ◽  
Conceptual Modeling ◽  
Semantic Integration ◽  
Information Systems Development ◽  
Business Managers ◽  
Modeling Approach ◽  
Evolutionary Changes ◽  
Dynamic Views ◽  
Structural Aspects

Most information systems development methodologies are based on conceptual modeling of static and dynamic views, which are represented by totally different types of diagrams. Understanding of the interplay among interactive, behavioral and structural aspects of specifications is necessary for identification of semantic integrity problems between business process and business data. Typically, semantic inconsistencies and discontinuities between collections of conceptual representations are not easy to detect and to comprehend for information system designers due to static and dynamic aspects of models being visualized in isolation. The goal of this paper is to present a modeling approach for semantic integration and evolution of static and dynamic aspects of conceptual models. Visualization of interplay among structural, interactive and behavioral aspects of computation-neutral representations helps to understand crosscutting concerns and integrity problems of information system conceptualizations. The main advantage of the presented conceptual modeling approach is stability and flexibility of diagrams in dealing with the evolutionary changes of requirements. Therefore, the developed modeling foundation is targeted to both business managers and information system designers for the purpose of computation-neutral integration and evolution of information systems specifications.

scholarly journals Selected Topics on Enablers for Next-Generation Information Systems Development: Editorial Introduction to Issue 25 of CSIMQ

2020 ◽  
pp. I-II
Author(s):  
Robert Andrei Buchmann ◽  
Keyword(s):  
Information Systems ◽  
Industry 4.0 ◽  
Design Science ◽  
Conceptual Modeling ◽  
Systems Development ◽  
Assessment Model ◽  
Information Systems Development ◽  
Modeling Languages ◽  
Domain Specific Modeling ◽  
Specific Modeling

The 25th issue of CSIMQ presents four articles that investigate novel enablers for information systems development. Three of the selected articles focus on conceptual modeling methods, whereas the fourth one investigates the readiness of SMEs for Industry 4.0 adoption. Model-driven engineering was both tailored (on method level) and applied in two of the papers, taking a Design Science approach to develop proofs-of-concept for the notion of “technology-specific modeling”, a particular flavor of domain-specific modeling – more precisely, technology-specific modeling languages reflect the specificity of a technological ecosystem or pattern (e. g. REST APIs, MVC Web development frameworks). The third paper's contribution may also be seen as a modeling method, although it is not framed as such – it focuses on a design viewpoint and its theoretical applicability in business scenarios. This method proposes a chemistry-inspired technique for optimizing enterprise collaboration patterns based on their KPI effects. Finally, the last paper takes a systematic literature review approach to investigate Industry 4.0 adoption at SME level through the lens of a modified version of the IMPULS assessment model.

A Meta-Analysis of Ontological Guidance and Users' Understanding of Conceptual Models

2020 ◽  
Vol 31 (4) ◽  
pp. 46-68
Author(s):  
Arash Saghafi ◽  
Yair Wand
Keyword(s):  
Information Systems ◽  
Conceptual Models ◽  
Meta Analysis ◽  
Conceptual Modeling ◽  
Information Systems Success ◽  
Modeling Process ◽  
Real World Applications ◽  
The Impact ◽  
Do So

Information systems are intended to be faithful accounts of real-world applications. As an integral part of the development process, analysts create conceptual models in order to understand the application and communicate requirements. Failure to do so has been a prominent reason for IT projects' failure. Hence, improving the quality of models could have a major impact on the information systems' success. To guide the modeling process, researchers use ontology to create more expressive representations of reality. However, improving expressiveness can make the models complicated and cause cognitive hurdles for users. Therefore, the question is whether ontological guidance is worth the trade-off between expressiveness and complexity. This paper describes a meta-analysis of empirical research examining the impact of ontological guidance on users' understandability. The results show that ontological guidance can improve users' understanding of conceptual models, especially those requiring deeper understanding, thus providing support for ontological guidance in conceptual modeling.

scholarly journals THE CASE FOR A COUPLED USER-ORIENTED PROCESS (RE)DESIGN AND INFORMATION SYSTEMS DEVELOPMENT

2020 ◽  
Author(s):  
Maja Ćukušić ◽  
Keyword(s):  
Information Systems ◽  
Process Management ◽  
Conceptual Models ◽  
Systems Development ◽  
Information Systems Development ◽  
New Approach ◽  
Customer Experience Management ◽  
Private And Public ◽  
Public Organisations ◽  
Smart Technologies

The paper synthesises studies of two specific conceptual models from a rather wide area of user-oriented process (re)design and the development of related, modern information systems based on smart technologies. Further, it proposes a new approach for coupling (1) a methodology for convergent customer experience management and business process management, with (2) a framework for user-oriented data-driven information systems development. It also analyses the implications and conditions for its implementation in private and public organisations.

scholarly journals Institutional ontology for Conceptual Modeling

2018 ◽  
Vol 33 (2) ◽  
pp. 105-123 ◽  
Author(s):  
Owen Eriksson ◽  
Paul Johannesson ◽  
Maria Bergholtz
Keyword(s):  
Information Systems ◽  
Ontological Commitment ◽  
Conceptual Models ◽  
Conceptual Modeling ◽  
Systems Design ◽  
Alternative View ◽  
Systems Research ◽  
Information Infrastructures ◽  
The World ◽  
Institutional Reality

Conceptual models are intended to capture knowledge about the world. Hence, the design of conceptual models could be informed by theories about what entities exist in the world and how they are constituted. Further, a common assumption within the field of conceptual modeling is that conceptual models and information systems describe entities in the real world, outside the systems. An alternative view is provided by an ontological commitment that recognizes that the institutional world is constructed through language use and the creation of institutional facts. Such an ontological commitment implies that there is an institutional reality, which, to a great extent, is constructed using information infrastructures. Accordingly, conceptual models have not only a descriptive role but also a prescriptive one, meaning that modelers set up a framework of rules that restrict and enable people to construct institutional reality using information infrastructures. Understanding the prescriptive role of conceptual models may revive the area of conceptual modeling in the information systems research community. Reviving conceptual modeling through institutional modeling is motivated by the effect that implemented conceptual models have on information infrastructures and institutions. The purpose of this article is to propose an institutional ontology that can support the design of information infrastructures. The ontology is theoretically informed by institutional theory and a communicative perspective on information systems design, as well as being empirically based on several case studies. It is illustrated using a case study in the welfare sector. A number of guidelines for modeling institutional reality are also proposed.

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