How do individuals decide which modeling scripts to use during systems analysis and design?

Abstract Because most information systems in real-world domains are complex, practitioners often use different types of conceptual modeling scripts to understand them. Modeling methods such as UML, for example, provide more than a dozen scripts for practitioners to use. We study how script readers decide which scripts to use during systems analysis and design tasks. We carried out a free-simulation experiment to test how users select scripts based on two factors: combined ontological completeness and ontological overlap. We find that participants indeed decided to select more than one script to achieve a more complete domain representation. But, when they selected more than three scripts, they decided to remove scripts and reduce combined completeness to increase the clarity of the representation. Our results indicate that script readers prefer relatively less complete scripts with high levels of clarity over more complete, but more overlapping, script combinations. We detail the implications these findings have for the theory and the practice of conceptual modeling.

[1]  Andrew Gemino,et al.  A framework for empirical evaluation of conceptual modeling techniques , 2004, Requirements Engineering.

[2]  Joerg Evermann,et al.  Ontological Modeling Rules for UML: An Empirical Assessment , 2006, J. Comput. Inf. Syst..

[3]  Marta Indulska,et al.  How do practitioners use conceptual modeling in practice? , 2006, Data Knowl. Eng..

[4]  Graeme G. Shanks,et al.  Representing part-whole relations in conceptual modeling: an empirical evaluation , 2008 .

[5]  Jan Recker,et al.  Continued use of process modeling grammars: the impact of individual difference factors , 2010, Eur. J. Inf. Syst..

[6]  Andrew Gemino,et al.  Evaluating modeling techniques based on models of learning , 2003, CACM.

[7]  Jan Mendling,et al.  How visual cognition influences process model comprehension , 2017, Decis. Support Syst..

[8]  Mark Rouncefield,et al.  Model-driven engineering practices in industry: Social, organizational and managerial factors that lead to success or failure , 2014, Sci. Comput. Program..

[9]  Ron Weber,et al.  Research Commentary: Information Systems and Conceptual Modeling - A Research Agenda , 2002, Inf. Syst. Res..

[10]  Jinwoo Kim,et al.  How Do We Understand a System with (So) Many Diagrams? Cognitive Integration Processes in Diagrammatic Reasoning , 2000, Inf. Syst. Res..

[11]  Joey F. George,et al.  Modern Systems Analysis and Design , 1996 .

[12]  Mark Strembeck,et al.  Factors of process model comprehension - Findings from a series of experiments , 2012, Decis. Support Syst..

[13]  Marta Indulska,et al.  A Reference Methodology for Conducting Ontological Analyses , 2004, ER.

[14]  Kalle Lyytinen,et al.  Information systems development and data modelling: conceptual and philosophical foundations , 1995 .

[15]  Marian Petre,et al.  UML in practice , 2013, 2013 35th International Conference on Software Engineering (ICSE).

[16]  Iris Vessey,et al.  Learning to Specify Information Requirements: The Relationship between Application and Methodology , 1993, J. Manag. Inf. Syst..

[17]  Jan Mendling,et al.  An Empirical Review of the Connection Between Model Viewer Characteristics and the Comprehension of Conceptual Process Models , 2019, Inf. Syst. Frontiers.

[18]  Katrin Bittrich,et al.  Laboratory Experimentation , 2020, Encyclopedia of Personality and Individual Differences.

[19]  Dag I. K. Sjøberg,et al.  Evaluating the effect of a delegated versus centralized control style on the maintainability of object-oriented software , 2004, IEEE Transactions on Software Engineering.

[20]  Daniel L. Moody,et al.  The “Physics” of Notations: Toward a Scientific Basis for Constructing Visual Notations in Software Engineering , 2009, IEEE Transactions on Software Engineering.

[21]  Marta Indulska,et al.  Business Process Modeling- A Comparative Analysis , 2009, J. Assoc. Inf. Syst..

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

[23]  Marta Indulska,et al.  Information Systems as Representations: A Review of the Theory and Evidence , 2019, J. Assoc. Inf. Syst..

[24]  Joselaine Valaski,et al.  Deriving Domain Functional Requirements from Conceptual Model Represented in OntoUML , 2017, ICEIS.

[25]  Marta Indulska,et al.  Candidate interoperability standards: An ontological overlap analysis , 2007, Data Knowl. Eng..

[26]  Jan Mendling,et al.  Syntax highlighting in business process models , 2011, Decis. Support Syst..

[27]  Jeffrey Parsons,et al.  How UML is used , 2006, CACM.

[28]  Giancarlo Guizzardi,et al.  An ontology-based analysis and semantics for organizational structure modeling in the ARIS method , 2013, Inf. Syst..

[29]  Steven L. Alter,et al.  A Broad View of Systems Analysis and Design: Implications for Research , 2005, Commun. Assoc. Inf. Syst..

[30]  Peter Green,et al.  How do Individuals Interpret Multiple Conceptual Models? A Theory of Combined Ontological Completeness and Overlap , 2019, J. Assoc. Inf. Syst..

[31]  Andrew Gemino,et al.  Use Case Diagrams in Support of Use Case Modeling: Deriving Understanding from the Picture , 2009, J. Database Manag..

[32]  Akhil Kumar,et al.  Conceptual model for online auditing , 2011, Decis. Support Syst..

[33]  Isabelle Comyn-Wattiau,et al.  A UML-based data warehouse design method , 2006, Decis. Support Syst..

[34]  James D. Thompson.  Organizations in Action: Social Science Bases of Administrative Theory , 1967 .

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

[36]  Brian Henderson-Sellers,et al.  Ontological Evaluation of the UML Using the Bunge–Wand–Weber Model , 2002, Software and Systems Modeling.

[37]  Wil M. P. van der Aalst,et al.  From conceptual process models to running systems: A holistic approach for the configuration of enterprise system processes , 2008, Decis. Support Syst..

[38]  Peter Meso,et al.  The Effects of Decomposition Quality and Multiple Forms of Information on Novices' Understanding of a Domain from a Conceptual Model , 2008, J. Assoc. Inf. Syst..

[39]  Jan Recker,et al.  Exploring cognitive style and task-specific preferences for process representations , 2016, Requirements Engineering.

[40]  Keng Siau.  An Analysis of Unified Modeling Language ( UML ) Graphical Constructs Based on BWW Ontology , 2009 .

[41]  Jan Recker,et al.  Combined Use of Conceptual Models in Practice: An Exploratory Study , 2017, J. Database Manag..

[42]  Ivar Jacobson,et al.  The Unified Modeling Language User Guide , 1998, J. Database Manag..

[43]  Rita Almeida Ribeiro,et al.  A framework for dynamic multiple-criteria decision making , 2011, Decis. Support Syst..

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

[45]  P. Chandler,et al.  Why Some Material Is Difficult to Learn , 1994 .

[46]  Julie E. Kendall,et al.  Systems analysis and design , 1981 .

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

[48]  Jan Mendling,et al.  Enhancing understandability of process models through cultural-dependent color adjustments , 2016, Decis. Support Syst..

[49]  Joerg Evermann,et al.  Ontology based object-oriented domain modelling: fundamental concepts , 2005, Requirements Engineering.

[50]  Jan Mendling,et al.  A study on the effects of routing symbol design on process model comprehension , 2013, Decis. Support Syst..

[51]  R. Mayer.  Thinking, Problem Solving, Cognition , 1983 .

[52]  Søren Lauesen,et al.  Preventing Requirement Defects: An Experiment in Process Improvement , 2001, Requirements Engineering.

[53]  Geert Poels,et al.  Creation of Multiple Conceptual Models from User Stories - A Natural Language Processing Approach , 2019, ER Workshops.

[54]  Rajiv Kishore,et al.  Agile Integration Modeling Language (AIML): A conceptual modeling grammar for agile integrative business information systems , 2007, Decis. Support Syst..

[55]  Corin A. Gurr,et al.  Effective Diagrammatic Communication: Syntactic, Semantic and Pragmatic Issues , 1999, J. Vis. Lang. Comput..

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

[57]  Marta Indulska,et al.  Complementary Use of Modeling Grammars , 2011, Scand. J. Inf. Syst..

[58]  Arne Sølvberg,et al.  Understanding quality in conceptual modeling , 1994, IEEE Software.

[59]  Yair Wand,et al.  Conceptualizing Routing Decisions in Business Processes: Theoretical Analysis and Empirical Testing , 2015, J. Assoc. Inf. Syst..

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

[61]  Ron Weber,et al.  Ontological foundations of information systems , 1997 .

[62]  Jeffrey Parsons,et al.  Dimensions of UML Diagram Use: A Survey of Practitioners , 2008, J. Database Manag..

[63]  Jan Recker,et al.  How Much Language Is Enough? Theoretical and Practical Use of the Business Process Modeling Notation , 2008, CAiSE.

[64]  Gretchen Irwin,et al.  An Ontological Analysis of Use Case Modeling Grammar , 2005, J. Assoc. Inf. Syst..

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

[66]  Mark Rouncefield,et al.  The State of Practice in Model-Driven Engineering , 2014, IEEE Software.

[67]  Peter Fettke,et al.  How Conceptual Modeling Is Used , 2009, Commun. Assoc. Inf. Syst..

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

[69]  Ned Kock,et al.  Communication flow orientation in business process modeling and its effect on redesign success: Results from a field study , 2009, Decis. Support Syst..

[70]  Peter Meso,et al.  Conceptualizing Systems for Understanding: An Empirical Test of Decomposition Principles in Object-Oriented Analysis , 2006, Inf. Syst. Res..

[71]  Julie Pallant,et al.  SPSS survival manual : a step by step guide to data analysis using SPSS for Windows , 2001, Behaviour Change.

[72]  Arturo Castellanos,et al.  From Representation to Mediation: A New Agenda for Conceptual Modeling Research in a Digital World , 2020, MIS Q..

[73]  Jan Mendling,et al.  The Influence of Business Process Representation on Performance of Different Task Types , 2019, J. Inf. Syst..

[74]  Alberto Rodrigues da Silva,et al.  Model-driven engineering: A survey supported by the unified conceptual model , 2015, Comput. Lang. Syst. Struct..

[75]  Jan Recker,et al.  "Modeling with tools is easier, believe me" - The effects of tool functionality on modeling grammar usage beliefs , 2012, Inf. Syst..

[76]  Keng Siau,et al.  Theoretical vs. Practical Complexity: The Case of UML , 2005, J. Database Manag..

[77]  Marta Indulska,et al.  Using ontology for the representational analysis of process modelling techniques , 2009, Int. J. Bus. Process. Integr. Manag..

[78]  Roger J. Brooks,et al.  Choosing the best model: Level of detail, complexity, and model performance , 1996 .

[79]  Venkataraman Ramesh,et al.  Human Factors Research on Data Modeling: A Review of Prior Research, An Extended Framework and Future Research Directions , 2002, J. Database Manag..

[80]  David Whiteley,et al.  An Introduction to Information Systems , 2013 .