1. Information Technology IMS5024 Information Systems Modelling Lecture 1 Modelling and ISD

2. School of Information Management & Systems 1.2 Contents Welcome, Introductions and housekeeping Approach What is Modelling?

3. School of Information Management & Systems 1.3 Lecturers Unit-Coordinator Andrew Barnden Building S, 7-14 Phone: 99032469 E-mail: andrew.barnden@sims. monash.edu.au andrew.barnden@sims. monash.edu.au Dr Helana Scheepers Building S, 4-10 Phone: 99031066 E-mail: helana.scheepers@sims. monash.edu.au helana.scheepers@sims. monash.edu.au

4. School of Information Management & Systems 1.4 Unit outline Unit home page http://www.sims.monash.edu.au/subjects/IMS5024 Objectives Assessment Pass requirements the astute student

5. School of Information Management & Systems 1.5 Pass requirements 50% or more of the total available marks in addition, these conditions apply minimum 40% of the examination marks AND minimum 40% of the assignment marks

6. School of Information Management & Systems 1.6 The Astute Student will: attend every lecture and every tutorial read the reference material before lectures and tutorials listen to what the lecturers say NOT memorise the overhead slides, but instead, investigate and form opinions about the slide topics ask questions

7. School of Information Management & Systems 1.7 Assessment Modelling research report Synopsis for evaluation in week 3 Due Week 6 Object oriented modelling assignment Due Week 11 Exam

8. School of Information Management & Systems 1.8 Pitfalls Read website regularly for updates on reading, class assignments and announcements Plagiarism http://www.sims.monash.edu.au/policies/plagiarism.html offenders will get caught

9. School of Information Management & Systems 1.9 Lecture 1: Chapter 2 of Veryard, R (1992). Information Modelling: Practical Guidance, Prentice Hall International, UK. Lecture 2: Chapter 2 and 3 of Mathiassen, L and Dahlbom, B. (1993). Computers in Context: The philosophy and practice of systems design, Blackwell Publishers, UK. Chapter 2 of Hirschheim, R., Klein, H. and Lyytinen, K. (1995) Information Systems Development and Data Modelling: Conceptual and Philosophical Foundations, Cambridge University Press Reading

10. School of Information Management & Systems 1.10 Mathematical an equation; (eg. E=mc 2) Symbolic/Visual a theory; (eg. the theory of relativity) a hypothesis; (eg. the speed of light is not a limiting velocity) an analogy; (eg. a map) Physical/Iconic an artefact; (eg. a model car) What is a model?

11. School of Information Management & Systems 1.11 1. Scaling Down; both in terms of size and complexity 2. Transfer Across; representation in relative position 3. Workability; in principle the model operates like the original as a consequence of 1&2 4. Appropriateness; to the aspect of reality under investigation The nature of models

12. School of Information Management & Systems 1.12 The model is the reality The model represents all of reality The pathology of modelling

13. School of Information Management & Systems 1.13 Models are an agreed “language” by which a diverse group can communicate about an essential aspect of the “Universe of Discourse” (UoD) It facilitates communication, and shared understanding, between people who have a different perspective about an aspect of reality in which they have mutual interest. Why models are used

14. School of Information Management & Systems 1.14 A descriptive, narrative model - the big picture An aesthetic model - what will it look like An environmental model - where does it fit into the world A designer’s model - how does it fit together A fabricator’s model - what components are needed A builder’s model - what do we have to build it on A constructor’s model - how do we put it together Models as a means of communication

15. School of Information Management & Systems 1.15 Client/user Analyst Specs Programmer The problem of communication: views from the coalface

16. School of Information Management & Systems 1.16 Systems development is the process of modelling those aspects of the user’s physical requirements which can take advantage of the things a computer can do. The art of the analyst/designer is to convert what the users need to support their work into the form of instructions which a computer can follow What is systems development?

17. School of Information Management & Systems 1.17 Data Process Task Design Organisational Design Objects Events The Discourse of ISD

18. School of Information Management & Systems 1.18 StrengthsWeaknesses SimplifyOmit detail Relate to a particular purposesInaccurate (for some things) Relate to a specific audiencesIncomprehensible (to some audiences) No single model can accurately communicate information about ALL aspects of an information system. Strengths & weaknesses of ALL forms of modelling

19. School of Information Management & Systems 1.19 The analyst is interested in the “essential” model that depicts the essence of the system; what it must do independent of the technology or the actual system. To achieve this the analyst engages in a process of abstraction, which also includes generalisation, to identify the logical equivalent of the physical world. When modelled, such logical equivalents are called logical or conceptual models. The significance of conceptual models is that software can only represents such models and not the physical world. The concept of the logical equivalence

20. School of Information Management & Systems 1.20 engineering systems are much easier to model than information systems what gets modelled is what gets built (and remember all models omit some detail!) some things are easier to model than others some things are un-modellable some models are un-buildable systems development requires a large variety of models to meet the needs of different audiences Implications of systems modelling

21. School of Information Management & Systems 1.21 Using Models The analyst needs to; beware of simple modelling solutions (real organisations are not simple) think about the things which are too complex and/or can't be modelled beware of 'engineering' approaches to non- engineering systems