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.

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.

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.

The REA Pattern, Knowledge Structures, and Conceptual Modeling Performance

2005 ◽  
Vol 19 (2) ◽  
pp. 57-77 ◽  
Author(s):  
Gregory J. Gerard
Keyword(s):  
Domain Knowledge ◽  
Conceptual Models ◽  
Conceptual Modeling ◽  
Knowledge Structure ◽  
Specific Pattern ◽  
Accounting Information Systems ◽  
Domain Specific ◽  
Domain Specific Knowledge ◽  
Business Setting ◽  
Structured Knowledge

Most database textbooks on conceptual modeling do not cover domainspecific patterns. The texts emphasize notation, apparently assuming that notation enables individuals to correctly model domain-specific knowledge acquired from experience. However, the domain knowledge acquired may not aid in the construction of conceptual models if it is not structured to support conceptual modeling. This study uses the Resources Events Agents (REA) pattern as an example of a domain-specific pattern that can be encoded as a knowledge structure for conceptual modeling of accounting information systems (AIS), and tests its effects on the accuracy of conceptual modeling in a familiar business setting. Fifty-three undergraduate and forty-six graduate students completed recall tasks designed to measure REA knowledge structure. The accuracy of participants' conceptual models was positively related to REA knowledge structure. Results suggest it is insufficient to know only conceptual modeling notation because structured knowledge of domain-specific patterns reduces design errors.

Supporting Electronic Collaboration in Conceptual Modeling

2010 ◽  
pp. 199-211
Author(s):  
Peter Rittgen
Keyword(s):  
Conceptual Models ◽  
Conceptual Modeling ◽  
Negotiation Process ◽  
Distributed Development ◽  
Collaborative Modeling ◽  
Electronic Collaboration ◽  
The Social

The authors study collaborative modeling by analyzing conversations and loud thinking during modeling sessions and the resulting models themselves. They identify the basic activities of the modeling teams on the social, pragmatic, semantic and syntactic levels and derive a schema for the pragmatic level. The authors’ main conclusion is that team-based modeling is largely a negotiation process. Drawing on these results the authors derive an architecture of a system that supports the distributed development of conceptual models.

An Enterprise Ontology Based Conceptual Modeling Grammar for Representing Value Chain and Supply Chain Scripts

2016 ◽  
pp. 119-137
Author(s):  
Wim Laurier ◽  
Geert Poels
Keyword(s):  
Supply Chain ◽  
Value Chain ◽  
Conceptual Modeling ◽  
Third Party ◽  
Agent Model ◽  
Business Modeling ◽  
Business Partners ◽  
System Interoperability ◽  
Conceptual Modeling Grammar ◽  
Enterprise Ontology

In business modeling the focus is shifting from individual enterprises to the supply chains in which they collaborate. Contemporary business modeling grammars should allow each enterprise taking part in a supply chain to develop its own information system and at the same time support the creation of system interoperability and information sharing amongst business partners in the supply chain. This paper presents a conceptual modeling grammar for representing business scripts in a way that is both observer-dependent and independent. That is, value chain information should be represented in a format that is suitable for the perspective of any partner in the supply chain (e.g., enterprise, supplier, customer, customer's customer, supplier's supplier) and for the perspective of a completely neutral third party (e.g., government). The proposed observer-independent conceptual-modeling grammar, which is given strength by grounding it in the mature Resource-Event-Agent model, is shown to represent information about business phenomena of diverse supply chain partners such that it can be integrated across enterprise boundaries

Semantics of the MibML Conceptual Modeling Grammar

2007 ◽  
Vol 18 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Hong Zhang ◽  
Rajiv Kishore ◽  
Ram Ramesh
Keyword(s):  
Conceptual Modeling ◽  
Conceptual Modeling Grammar

Conceptual Modeling for Data Warehouse and OLAP Applications

2011 ◽  
pp. 293-300
Author(s):  
Elzbieta Malinowski ◽  
Esteban Zimányi
Keyword(s):  
Data Warehouse ◽  
Conceptual Models ◽  
Conceptual Modeling ◽  
Relational Model ◽  
Data Warehouses ◽  
Logical Models ◽  
Levels Of Detail ◽  
On Line ◽  
State Of Affairs ◽  
Research Stage

The advantages of using conceptual models for database design are well known. In particular, they facilitate the communication between users and designers since they do not require the knowledge of specific features of the underlying implementation platform. Further, schemas developed using conceptual models can be mapped to different logical models, such as the relational, objectrelational, or object-oriented models, thus simplifying technological changes. Finally, the logical model is translated into a physical one according to the underlying implementation platform. Nevertheless, the domain of conceptual modeling for data warehouse applications is still at a research stage. The current state of affairs is that logical models are used for designing data warehouses, i.e., using star and snowflake schemas in the relational model. These schemas provide a multidimensional view of data where measures (e.g., quantity of products sold) are analyzed from different perspectives or dimensions (e.g., by product) and at different levels of detail with the help of hierarchies. On-line analytical processing (OLAP) systems allow users to perform automatic aggregations of measures while traversing hierarchies: the roll-up operation transforms detailed measures into aggregated values (e.g., daily into monthly sales) while the drill-down operation does the contrary. Star and snowflake schemas have several disadvantages, such as the inclusion of implementation details and the inadequacy of representing different kinds of hierarchies existing in real-world applications. In order to facilitate users to express their analysis needs, it is necessary to represent data requirements for data warehouses at the conceptual level. A conceptual multidimensional model should provide a graphical support (Rizzi, 2007) and allow representing facts, measures, dimensions, and different kinds of hierarchies.

Development of Data Warehouse Conceptual Models

2011 ◽  
pp. 1-23
Author(s):  
Laila Niedrite ◽  
Maris Solodovnikova Treimanis ◽  
Liga Grundmane
Keyword(s):  
Data Warehouse ◽  
Conceptual Models ◽  
Data Warehousing ◽  
Conceptual Modeling ◽  
Requirements Elicitation ◽  
Method Engineering ◽  
Data Warehouses ◽  
Engineering Approach ◽  
New Methods ◽  
Development Approach

There are many methods in the area of data warehousing to define requirements for the development of the most appropriate conceptual model of a data warehouse. There is no universal consensus about the best method, nor are there accepted standards for the conceptual modeling of data warehouses. Only few conceptual models have formally described methods how to get these models. Therefore, problems arise when in a particular data warehousing project, an appropriate development approach, and a corresponding method for the requirements elicitation, should be chosen and applied. Sometimes it is also necessary not only to use the existing methods, but also to provide new methods that are usable in particular development situations. It is necessary to represent these new methods formally, to ensure the appropriate usage of these methods in similar situations in the future. It is also necessary to define the contingency factors, which describe the situation where the method is usable.This chapter represents the usage of method engineering approach for the development of conceptual models of data warehouses. A set of contingency factors that determine the choice between the usage of an existing method and the necessity to develop a new one is defined. Three case studies are presented. Three new methods: userdriven, data-driven, and goal-driven are developed according to the situation in the particular projects and using the method engineering approach.

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