A Journey to BSO: Evaluating Earlier and More Recent Ideas of Mario Bunge as a Foundation for Information Systems and Software Development

A prominent theoretical foundation for IT analysis, design and development is general ontology - a branch of philosophy which studies what exists in reality. A widely used general ontology is BWW (Bunge-Wand-Weber) – based on ideas of the philosopher and physicist Mario Bunge, synthesized by Wand and Weber. It is regarded as a major contribution to conceptual modeling, database design, data collection design and information quality, as well as theory of IT. At the same time, the ontology was founded on an early subset of Bunge’s philosophy and Bunge’s ideas have evolved since then. An important question, therefore, is: do the more recent ideas expressed by Bunge call for a new ontology? In this paper we conduct an analysis of research by Bunge aiming at addressing this question. We compare the constructs of BWW with what we call Bunge’s Systemist Ontology (BSO) – a new ontology based on broader and more recent ideas developed by Bunge. Informed by this comparison we offer suggestions for ontology studies as well as future applications of Bunge in conceptual modeling and other areas of IT.

[1]  M. Bunge.  Systems Everywhere , 2018, Cybernetics and Applied Systems.

[2]  Oscar Pastor,et al.  An Ontological-Based Approach to Analyze Software Production Methods , 2008, UNISCON.

[3]  Nicola Guarino,et al.  Sweetening Ontologies with DOLCE , 2002, EKAW.

[4]  Simon K. Milton,et al.  Ontological Foundations of Representational Information Systems , 2007 .

[5]  Ron Weber,et al.  Thirty Years Later: Some Reflections on Ontological Analysis in Conceptual Modeling , 2017, J. Database Manag..

[6]  M. Bunge.  Finding philosophy in social science , 1996 .

[7]  C. Hempel.  Philosophy of Natural Science , 1966 .

[8]  Giancarlo Guizzardi,et al.  Towards an Ontology of Software Defects, Errors and Failures , 2018, ER.

[9]  Andrew Gemino,et al.  Complexity and clarity in conceptual modeling: Comparison of mandatory and optional properties , 2005, Data Knowl. Eng..

[10]  M. Bunge.  Chasing Reality: Strife over Realism , 2006 .

[11]  Ron Weber,et al.  Should Optional Properties Be Used in Conceptual Modelling? A Theory and Three Empirical Tests , 2001, Inf. Syst. Res..

[12]  Veda C. Storey,et al.  Evaluating Domain Ontologies , 2019, ACM Comput. Surv..

[13]  Ron Weber,et al.  Building Conceptual Modeling on the Foundation of Ontology , 2014, Computing Handbook, 3rd ed..

[14]  M. Bunge.  Treatise on basic philosophy , 1974 .

[15]  Jan Recker,et al.  Ontology- Versus Pattern-Based Evaluation of Process Modeling Languages: A Comparison , 2007, Commun. Assoc. Inf. Syst..

[16]  S. Caneva.  The problems of perception. , 1960, Fortschritte der psychosomatischen Medizin. Advances in psychosomatic medicine.

[17]  Ron Weber,et al.  Optional Properties Versus Subtyping in Conceptual Modeling: A Theory and Empirical Test , 1996, ICIS.

[18]  Boris Wyssusek,et al.  On Ontological Foundations of Conceptual Modelling , 2006, Scand. J. Inf. Syst..

[19]  Gerd Wagner,et al.  Towards ontological foundations for conceptual modeling: The unified foundational ontology (UFO) story , 2015, Appl. Ontology.

[20]  Yair Wand,et al.  Research Note - How Semantics and Pragmatics Interact in Understanding Conceptual Models , 2014, Inf. Syst. Res..

[21]  Ron Weber,et al.  An Ontological Analysis of some Fundamental Information Systems Concepts , 1988, ICIS.

[22]  Ron Weber,et al.  Mario Bunge's ontology as a formal foundation for information systems concepts , 1990 .

[23]  Sampath Jayarathna,et al.  Change Detection and Notification of Web Pages , 2019, ACM Comput. Surv..

[24]  M. Bunge.  Epistemology & Methodology II: Understanding the World , 1983 .

[25]  M. Bunge.  Emergence and Convergence: Qualitative Novelty and the Unity of Knowledge , 2003 .

[26]  Csaba Veres,et al.  Psychological Foundations for Concept Modeling , 2004, Diagrams.

[27]  Mario Bunge,et al.  Gravitational Waves and Spacetime , 2018 .

[28]  Yair Wand,et al.  Analyzing Variability of Software Product Lines Using Semantic and Ontological Considerations , 2014, CAiSE.

[29]  Nicola Guarino,et al.  Formal ontology, conceptual analysis and knowledge representation , 1995, Int. J. Hum. Comput. Stud..

[30]  Arash Saghafi,et al.  Do Ontological Guidelines Improve Understandability of Conceptual Models? A Meta-analysis of Empirical Work , 2014, 2014 47th Hawaii International Conference on System Sciences.

[31]  Haan,et al.  Between Two Worlds , 2016 .

[32]  Michael Rosemann,et al.  Enhancing the Expressiveness of the Bunge-Wand-Weber Ontology , 2005, AMCIS.

[33]  Brian Henderson-Sellers.  Why Philosophize; Why not Just Model? , 2015, ER.

[34]  Cesar Gonzalez-Perez.  How Ontologies Can Help in Software Engineering , 2015, GTTSE.

[35]  David Gefen,et al.  Toward Creating a General Ontology for Research Validity , 2019, ER Forum/Posters/Demos.

[36]  Ron Weber,et al.  Properties do not have Properties: Investigating a Questionable Conceptual Modelling Practice , 2003 .

[37]  Oscar Pastor,et al.  Applying the Principles of an Ontology-Based Approach to a Conceptual Schema of Human Genome , 2013, ER.

[38]  Oscar Pastor,et al.  Comparing traditional conceptual modeling with ontology-driven conceptual modeling: An empirical study , 2019, Inf. Syst..

[39]  M. Bunge.  Ethics: The Good and the Right , 1989 .

[40]  R. Espejo.  What is systemic thinking , 1994 .

[41]  Roman Lukyanenko,et al.  Representing instances: the case for reengineering conceptual modelling grammars , 2018, Eur. J. Inf. Syst..

[42]  M. Bunge.  Philosophy of Science: Volume 2, From Explanation to Justification , 1998 .

[43]  Eduard Babkin,et al.  Towards Devising an Architectural Framework for Enterprise Operating Systems , 2018, ICSOFT.

[44]  Ron Weber,et al.  On the ontological expressiveness of information systems analysis and design grammars , 1993, Inf. Syst. J..

[45]  Roman Lukyanenko,et al.  Representing Crowd Knowledge: Guidelines for Conceptual Modeling of User-generated Content , 2017, J. Assoc. Inf. Syst..

[46]  Roman Lukyanenko,et al.  The IQ of the Crowd: Understanding and Improving Information Quality in Structured User-Generated Content , 2014, Inf. Syst. Res..

[47]  M. Bunge.  Systemism: the alternative to individualism and holism , 2000 .

[48]  Richard Y. Wang,et al.  Anchoring data quality dimensions in ontological foundations , 1996, CACM.

[49]  Yair Wand,et al.  Emancipating instances from the tyranny of classes in information modeling , 2000, TODS.

[50]  Giancarlo Guizzardi,et al.  Ontological foundations for structural conceptual models , 2005 .

[51]  M. Bunge.  The Dark Side of Technological Progress , 2018, The Impact of Critical Rationalism.

[52]  Ron Weber,et al.  Toward a Theory of the Deep Structure of Information Systems , 1990, ICIS.

[53]  Marta Indulska,et al.  Assessing Representation Theory with a Framework for Pursuing Success and Failure , 2017, MIS Q..

[54]  H. Herre.  General Formal Ontology (GFO): A Foundational Ontology for Conceptual Modelling , 2010 .

[55]  Salvatore T. March,et al.  Toward a Social Ontology for Conceptual Modeling , 2014, Commun. Assoc. Inf. Syst..

[56]  Marta Indulska,et al.  Do Ontological Deficiencies in Modeling Grammars Matter? , 2011, MIS Q..

[57]  V. Ramesh,et al.  Exploring the Effects of Extensional Versus Intensional Representations on Domain Understanding , 2018, MIS Q..