Developing Ontological Theories for Conceptual Models using Qualitative Research

Conceptual modelling is believed to be at the core of the IS discipline. There have been attempts to develop theoretical foundations for conceptual models, in particular ontological models as axiomatic reference systems. Although the notion of ontology has become popular in modelling theories, criticism has risen as to its philosophical presuppositions. Taking on this criticism, we discuss the task of developing socially constructed ontologies for modelling domains and outline how to enhance the expressiveness of ontological modelling theories by developing them via qualitative research methods such as Grounded Theory

OntoEng: A design method for ontology engineering in information systems

This paper addresses the design problem relating to ontology engineering in the discipline of information systems. Ontology engineering is a realm that covers issues related to ontology development and use throughout its life span. Nowadays, ontology as a new innovation promises to improve the design, semantic integration, and utilization of information systems. Ontologies are the backbone of knowledge-based systems. In addition, they establish sharable and reusable common understanding of specific domains amongst people, information systems, and software agents. Notwithstanding, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. On the basis of the gathered experience during the development of V4 Telecoms Business Model Ontology as well as the conducted integration of the related literature from the design science paradigm, this paper introduces OntoEng and its application as a novel systematic design method for ontology engineering

Percieved Evaluability - Development of a Theoretical Model and a Measurement Scale

Sound conceptual models are commonly considered as an important factor for successful information systems (IS) development. Due to inaccurate conceptual specifications, IS projects can be delayed or even fail. Thus, thorough evaluation of models is a major concern in IS research. Consequently, theoretical models are required which elucidate the conditions for the successful evaluability of conceptual models. However, IS literature only provides little insights about the prerequisites of effective evaluation. Systematic investigations on the evaluability of conceptual models are missing. Therefore, is paper aims at two research results. Firstly, based on a comprehensive literature review we propose a theoretical model of perceived evaluability. This theoretical model rests on the influence of domain knowledge and the perceived comprehensibility of conceptual models as its two main impact factors. Secondly, to prepare an empirical evaluation of the theoretical model, the development of measurement scales is described. The first steps of this process are exemplified based on an inquiry of modeling experts and implications for testing our hypotheses are provide

Variations in Conceptual Modeling: Classification and Ontological Analysis

Conceptual models are aimed at providing formal representations of a domain. They are mainly used for the purpose of understanding and communicating about requirements for information systems.Conceptual modeling has acquired a large body of research dealing with the semantics of modeling constructs, with the goal to make models better vehicles for understanding and communication. However, it is commonly known that different people construct different models of a given domain although all may be similarly adequate. The premise of this paper is that variations in models reflect vagueness in the criteria for deciding how to map reality into modeling constructs. Exploring model variations as such can contribute to research that deals with the semantics of modeling constructs.This paper reports an exploratory study in which empirically obtained model variations were qualitatively analyzed and classified into variation types. In light of the identified variation types, we analyzed two ontology-based modeling frameworks in order to evaluate their potential contribution to a reduction in variations. Our analysis suggests that such frameworks may contribute to more conclusive modeling decision making, thus reducing variations. However, since there is no complete consistency between the two frameworks, in order to reduce variations, a single framework should be systematically applied

Graphical Research Models in the Information Systems Discipline

Graphical models facilitate communicating hypothesized or tested relationships between variables and are welcome in information systems publications. However, insufficient knowledge exists about design conventions for such models, lowering their communicative effectiveness. This paper investigates how graphical research models are used in the information systems literature. Theoretically, the article bears upon the perspective of prototypicality and cognitively effective design of conceptual modeling notations. Based on an analysis of 134 research models from 589 articles in information systems journals, we tentatively demonstrate prototypical features of visual research models and outline many unique graphical variations. We develop a set of hypotheses on how prototypicality influences preferences for research models and their comprehensibility and describe how we intend to test these hypotheses empirically. A broader goal of this research is to develop an effective modeling notation for research models to support researchers in constructing unambiguous visual models for their research

Institutionalization and Structuration: Studying the Links between Action and Institution

Institutional theory and structuration theory both contend that institutions and actions are inextricably linked and that institutionalization is best understood as a dynamic, ongoing process. Institutionalists, however, have pursued an empirical agenda that has largely ignored how institutions are created, altered, and reproduced, in part, because their models of institutionalization as a process are underdeveloped. Structuration theory, on the other hand, largely remains a process theory of such abstraction that it has generated few empirical studies. This paper discusses the similarities between the two theories, develops an argument for why a fusion of the two would enable institutional theory to significantly advance, develops a model of institutionalization as a structuration process, and proposes methodological guidelines for investigating the process empirically

The Knowledge Body of Requirement Engineering in IST Innovations: An Ontological Analysis

Requirement Engineering is considered a key factor for Information Systems and Technology (IST) success in innovation. After roughly 40 years, important questions about the impact of RE in innovations remains. Literature review and bibliometric reports are well-known techniques for describing the state of the art; however, both can cover what has been done, but fail to identify the less developed areas. An alternative method is used to describe the whole knowledge body of RE (KBoRE) for IST innovations, and then systematically identify the most, less and uncovered areas. This paper proposes an Ontological framework of the KBoRE for IST innovations, by decomposing it through the identification of taxonomies and concepts that represent the field. Then, we apply the ontology to map articles from SCOPUS and WoS databases. Results reveal emphases that help to design research agendas and feed the KBoRE for IST Innovations to fill the gaps between the academic curiosity and the industry progress

Recommendation-Based Conceptual Modeling and Ontology Evolution Framework (CMOE+)

Within an enterprise, various stakeholders create different conceptual models, such as process, data, and requirements models. These models are fundamentally based on similar underlying enterprise (domain) concepts, but they differ in focus, use different modeling languages, take different viewpoints, utilize different terminology, and are used to develop different enterprise artifacts; as such, they typically lack consistency and interoperability. This issue can be solved by enterprise-specific ontologies, which serve as a reference during the conceptual model creation. Using such a shared semantic repository makes conceptual models interoperable and facilitates model integration. The challenge to accomplish this is twofold: on the one hand, an up-to-date enterprise-specific ontology needs to be created and maintained, and on the other hand, different modelers also need to be supported in their use of the enterprise-specific ontology. The authors propose to tackle these challenges by means of a recommendation-based conceptual modeling and an ontology evolution framework, and we focus in particular on ontology-based modeling support. To this end, the authors present a framework for Business Process Modeling Notation (BPMN) as a conceptual modeling language, and focus on how modelers can be assisted during the modeling process and how this impacts the semantic quality of the resulting models. Subsequently, a first, large-scale explorative experiment is presented involving 140 business students to evaluate the BPMN instantiation of our framework. The experiments show promising results with regard to incurred overheads, intention of use and model interoperability

Refactoring software development process terminology through the use of ontology

In work that is ongoing, the authors are examining the extent of software development process terminology drift. Initial findings suggest there is a degree of term confusion, with the mapping of concepts to terms lacking precision in some instances. Ontologies are concerned with identifying the concepts of relevance to a field of endeavour and mapping those concepts to terms such that term confusion is reduced. In this paper, we discuss how ontologies are developed. We also identify various sources of software process terminology. Our work to date indicates that the systematic development of a software development process ontology would be of benefit to the entire software development community. The development of such an ontology would in effect represent a systematic refactoring of the terminology and concepts produced over four decades of software process innovation