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Visual Comparison of Enterprise Models Using Syntactic Model Information

Visual Comparison of Enterprise Models Using Syntactic Model Information. Jean-Paul Van Belle jvbelle@commerce.uct.ac.za. Why research "visualization of models"?. You get interesting results!. Slides,. waves. and roller-coasters. Research Objective.

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Visual Comparison of Enterprise Models Using Syntactic Model Information

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  1. Visual Comparison of Enterprise Models Using Syntactic Model Information Jean-Paul Van Belle jvbelle@commerce.uct.ac.za

  2. Why research "visualization of models"? You get interesting results! Visual Comparison of Enterprise Models ACIS'03

  3. Slides, waves androller-coasters Visual Comparison of Enterprise Models ACIS'03

  4. Research Objective • Find an immediately intuitivecharacterisation and visualization of the (syntactic & semantic) comparison of modelswithin a particular application domainNotes: • Descriptive – not normative (yet)! • Existing metrics not satisfactory • Real-world test bed Visual Comparison of Enterprise Models ACIS'03

  5. Overview • Introduction: The research context • Overview of the Enterprise Models • Problems with SE metrics for models • Graph analysis approach • Fan-out Frequency Distributionplot & signature • Visual interpretation of semantic distance Visual Comparison of Enterprise Models ACIS'03

  6. See also: Chris Taylor @ QUT Framework for Analysis & Evaluation of Models Visual Comparison of Enterprise Models ACIS'03

  7. The Model Database • Purpose: to serve as a validating test bank for the analysis framework. • Model Selection Criteria: • Domain = “The Generic Enterprise” • Sufficiently large size • ~200 entities; ~300 relationships • Publicly available • From very different reference disciplines Visual Comparison of Enterprise Models ACIS'03

  8. The Models: Systems Engineering • Reference Frameworks • Purdue • Nippon • ARRI • OO • BOMA • Fowler (patterns!) • San Francisco • ERD Libraries • Silverston • Hay Visual Comparison of Enterprise Models ACIS'03

  9. The Models: Practitioners • ERPs • BAAN • SAP R/3 • Real organisations • AKMA • NHS • Data warehousing • Inmon Visual Comparison of Enterprise Models ACIS'03

  10. The Models: Various • Ontologies • TOVE • CYC (subset) • AIAI • Miscellaneous • Miller (systems theory) • Ottawa (linguistic) • Random • Finance • Belgian Accounting • USB Growth Model Visual Comparison of Enterprise Models ACIS'03

  11. Non-visual approaches:Model metrics • Structural metrics relate to the number of nodes (entities) and arcs (relationships between the entities). • Inheritance metrics investigate the characteristics of the inheritance trees. • Grouper metrics take into account the modularity of the model by means of the grouper constructs Visual Comparison of Enterprise Models ACIS'03

  12. Structural metrics • McGabe’s cyclomatic complexityCC = # relationships - # entities + 1 • Relative connectivity= # relationships / # entities • DeMarco’s DataBang=  REi (# relationships for ith entity) x wi (ith entity’s weighting factor). Visual Comparison of Enterprise Models ACIS'03

  13. Visual Comparison of Enterprise Models ACIS'03

  14. Structural Metrics: Deficiencies • # Entities/Relationship: a rough size indicator but no proxy for complexity • Cyclomatic Complexity is meaningless (not normalized for model size!) • Relative connectivity & fanout are skewed by outliers • Data bang metrics are of little or no interpretative value Visual Comparison of Enterprise Models ACIS'03

  15. Visualizing Model Structure • Graph Analysis Packages • Plot of Fan-out Distributions • Descriptive Statistics • Proposed Fan-out Distribution Statistics Visual Comparison of Enterprise Models ACIS'03

  16. Graph Analysis Packages • The model as a directed graph or network • Many tools available • E.g. PAJEK: Package for Large network Analysis (Vlado Group, Univ Ljubljani, Slovenia) • Problem: visualization  “bunch of lines” • The key element = fan-outs! Visual Comparison of Enterprise Models ACIS'03

  17. BAAN Hay InmonSilverst. Visual Comparison of Enterprise Models ACIS'03

  18. Clustering (Fruchterman-Reingold) Visual Comparison of Enterprise Models ACIS'03

  19. "bunch of lines"Intuitive? Interpretation? • Essential element of complexity / syntactic structure = network • Essential element of network => connectivity or fan-out • Average fan-out => too simplistic • => Look at entire distribution of (entity) fan-outs Visual Comparison of Enterprise Models ACIS'03

  20. Plotting the Fan-out Frequency Distribution Visual Comparison of Enterprise Models ACIS'03

  21. Descriptive Statistical Measures • Central location (“average”) • Arithmetic; median; mode; harmonic • Dispersion (“spread”) • Standard deviation; range • Skewness (“ symmetry”) • 1st & 2nd Pearson coeff.; 3rd moment • Peakness / curtosis (“pointedness”) • Coeff. of curtosis; adjusted 4th moment Visual Comparison of Enterprise Models ACIS'03

  22. Visual Comparison of Enterprise Models ACIS'03

  23. Proposed Measures • Curve shape family • Waves  slides (& rollercoasters) • Bumpiness / smoothness • Number of inflexion points • Exceeding a minimum threshold (2.5%) • Degree of curvature (“bentness”) • Fit the cumulative freq distribution with y=tanh(x/h) function (1 param, good fit) Visual Comparison of Enterprise Models ACIS'03

  24. Slides, waves & roller-coasters Visual Comparison of Enterprise Models ACIS'03

  25. Plotting the Fan-out Frequency Distribution Visual Comparison of Enterprise Models ACIS'03

  26. Proposed Measures • Curve shape family • Waves  slides (& rollercoasters) • Bumpiness / smoothness • Number of inflexion points • Exceeding a minimum threshold (2.5%) • Degree of curvature (“bentness”) • Fit the cumulative freq distribution with y=tanh(x/h) function (1 param, good fit) Visual Comparison of Enterprise Models ACIS'03

  27. Visual Comparison of Enterprise Models ACIS'03

  28. Visual Comparison of Enterprise Models ACIS'03

  29. Syntactic  Semantic analysis • Syntactic=> appearance or shape of model network ("nodes & links") • Semantic=> meaning of network => partly captured in e.g. entity names=> "semantic overlap" (or distance) between models Visual Comparison of Enterprise Models ACIS'03

  30. Semantic Overlap Visual Comparison of Enterprise Models ACIS'03

  31. Semantic DistanceDendogram Visual Comparison of Enterprise Models ACIS'03

  32. Conclusions & Future Research • Traditional measures not very useful • Suggested measures seem to work very well for visualization • Normative interpretation? • Other domains? Visual Comparison of Enterprise Models ACIS'03

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  34. Visual Comparison of Enterprise Models ACIS'03

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