A Platform for a Pragmatic Metatheoretic Model for Information Systems Practice and Research

This work is motivated by the need for a firm foundation for analyses in support of a number of contemporary challenges facing the information systems (IS) profession and discipline in such areas as the management of digital identity and of data quality. This paper reviews alternative approaches to the three key components of metatheory that underlie theories and practices in the IS field: ontology, epistemology and the relatively new field of axiology, which is concerned with the notion of value. Mainstream assumptions about the researcher as an independent, value-free observer of phenomena are being undermined by recognition that researchers adopt one or more perspectives, most commonly of a single stakeholder, that the inherent bias in most research is towards the particular value-sets of the favoured stakeholders, and that this needs to be acknowledged, reflected and allowed for when drawing inferences from reported research. In order to support the categories of research that are the motivation for the p esent work, a pragmatic metatheoretic model is proposed, which approximates and articulates a layman\u27s \u27common sense\u27 interpretation. It comprises a working set of assumptions in each of the areas of ontology, epistemology and axiology. The model is relevant to IS practice, and to that portion of IS research activity that is intended to be relevant to IS practice

theory and empirical test

Successful information systems (IS) development requires the under- standing of the real world domain in which the IS is situated in and of which it is a representation. Developing such an understanding is the role of systems analy- sis, the first major step in IS development. Conceptual models developed during systems analysis are used to support understanding of and communication about the real world domain. Recent years have seen the emergence of the object-oriented approach in general and UML special cally for IS design and implementation. However, no generally accepted modelling language has been proposed for use during IS analysis. This study will examine the suitability of UML as a conceptual modelling lan- guage. This study comprises two parts. The first part studies UML from an ontological perspective, attaches real- world semantics and derives ontologically grounded rules for applying UML to conceptual modelling. It is argued that by following these rules, modellers will improve the performance of the resultant models. In a second step, the derived rules and proposed advantages must be empirically supported. An experimental study is designed for this purpose

Improving the Semantics of Conceptual-Modeling Grammars: A New Perspective on an Old Problem

A core activity in information systems development involves understanding the conceptual model of the domain that the information system supports. Any conceptual model is ultimately created using a conceptual-modeling (CM) grammar. Accordingly, just as high quality conceptual models facilitate high quality systems development, high quality CM grammars facilitate high quality conceptual modeling. This paper seeks to provide a new perspective on improving the quality of CM grammar semantics. For the past twenty years, the leading approach to this topic has drawn on ontological theory. However, the ontological approach captures just half of the story. It needs to be coupled with a logical approach. We show how ontological quality and logical quality interrelate and we outline three contributions of a logical approach: the ability to see familiar conceptual-modeling problems in simpler ways, the illumination of new problems, and the ability to prove the benefit of modifying CM grammars

Using ontology for the representational analysis of process modelling techniques

Selecting an appropriate business process modelling technique forms an important task within the methodological challenges of a business process management project. While a plethora of available techniques has been developed over the last decades, there is an obvious shortage of well-accepted reference frameworks that can be used to evaluate and compare the capabilities of the different techniques. Academic progress has been made at least in the area of representational analyses that use ontology as a benchmark for such evaluations. This paper reflects on the comprehensive experiences with the application of a model based on the Bunge ontology in this context. A brief overview of the underlying research model characterizes the different steps in such a research project. A comparative summary of previous representational analyses of process modelling techniques over time gives insights into the relative maturity of selected process modelling techniques. Based on these experiences suggestions are made as to where ontology-based representational analyses could be further developed and what limitations are inherent to such analyses

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

All rights reserved. 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

A Framework for Executable Systems Modeling

Systems Modeling Language (SysML), like its parent language, the Unified Modeling Language (UML), consists of a number of independently derived model languages (i.e. state charts, activity models etc.) which have been co-opted into a single modeling framework. This, together with the lack of an overarching meta-model that supports uniform semantics across the various diagram types, has resulted in a large unwieldy and informal language schema. Additionally, SysML does not offer a built in framework for managing time and the scheduling of time based events in a simulation. In response to these challenges, a number of auxiliary standards have been offered by the Object Management Group (OMG); most pertinent here are the foundational UML subset (fUML), Action language for fUML (Alf), and the UML profile for Modeling and Analysis of Real Time and Embedded Systems (MARTE). However, there remains a lack of a similar treatment of SysML tailored towards precise and formal modeling in the systems engineering domain. This work addresses this gap by offering refined semantics for SysML akin to fUML and MARTE standards, aimed at primarily supporting the development of time based simulation models typically applied for model verification and validation in systems engineering. The result of this work offers an Executable Systems Modeling Language (ESysML) and a prototype modeling tool that serves as an implementation test bed for the ESysML language. Additionally a model development process is offered to guide user appropriation of the provided framework for model building

A framework for information integration using ontological foundations

With the increasing amount of data, ability to integrate information has always been a competitive advantage in information management. Semantic heterogeneity reconciliation is an important challenge of many information interoperability applications such as data exchange and data integration. In spite of a large amount of research in this area, the lack of theoretical foundations behind semantic heterogeneity reconciliation techniques has resulted in many ad-hoc approaches. In this thesis, I address this issue by providing ontological foundations for semantic heterogeneity reconciliation in information integration. In particular, I investigate fundamental semantic relations between properties from an ontological point of view and show how one of the basic and natural relations between properties – inferring implicit properties from existing properties – can be used to enhance information integration. These ontological foundations have been exploited in four aspects of information integration. First, I propose novel algorithms for semantic enrichment of schema mappings. Second, using correspondences between similar properties at different levels of abstraction, I propose a configurable data integration system, in which query rewriting techniques allows the tradeoff between accuracy and completeness in query answering. Third, to keep the semantics in data exchange, I propose an entity preserving data exchange approach that reflects source entities in the target independent of classification of entities. Finally, to improve the efficiency of the data exchange approach proposed in this thesis, I propose an extended model of the column-store model called sliced column store. Working prototypes of the techniques proposed in this thesis are implemented to show the feasibility of realizing these techniques. Experiments that have been performed using various datasets show the techniques proposed in this thesis outperform many existing techniques in terms of ability to handle semantic heterogeneities and performance of information exchange

The utility of analogy in systems sciences

The structure of the thesis reflects the three main areas of investigation. The legitimacy of analogy as a systems concept, the derivation of a model of analogy for systems thinkers and the description of a framework for practice. In the first section we are concerned with establishing an appreciation and understanding of the potential utility in the concept of analogy for systems thinkers. Having briefly surveyed the history of analogy in systems thinking and acknowledging the CUITent methodological interest in metaphor we note that our interest in analogy has been a target for our critics and led to a loss of credibility. The thesis calls for a re-evaluation of this situation and we hence describe a system thinker's view of science as the grounds on which the utility of analogy is normally dismissed. The first three chapters show that the basis on which science attacks analogy as invalid and inappropriate is itself contentious and that identified 'weaknesses' in the scientific framework can become strengths in the re-conceptualisation of a model of analogy. We consider and distinguish the dynamic relationships between analogy, model and metaphor. In the second section having established the potential value of analogy as a concept, the thesis develops an explanation of how a model of analogy for systems thinkers can be conceptualised. In the development of the model we will consider particular implications of three types of analogy, 'positive', 'negative' and 'neutral' analogy and discuss the suggestion that they reveal possibilities for exploring different and contrasting rationalities; these issues will be discussed looking at the relationship between analogy and rationality and in this context the validity of the argument from analogy. In the final section the thesis asserts that that systems thinking should not shy away from explicit use of analogy and shows how can use the framework of analogy to reconceptualise systems concepts