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An enterprise architecture framework for multi-attribute information systems analysis

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Abstract

Enterprise architecture is a model-based IT and business management discipline. Enterprise architecture analysis concerns using enterprise architecture models for analysis of selected properties to provide decision support. This paper presents a framework based on the ArchiMate metamodel for the assessment of four properties, viz., application usage, system availability, service response time and data accuracy. The framework integrates four existing metamodels into one and implements these in a tool for enterprise architecture analysis. The paper presents the overall metamodel and four viewpoints, one for each property. The underlying theory and formalization of the four viewpoints is presented. In addition to the tool implementation, a running example as well as guidelines for usage makes the viewpoints easily applicable.

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Notes

  1. Pre-print, revision submitted to the Journal of Strategic Information Systems, manuscript available for review upon request.

  2. http://www.ics.kth.se/eat.

References

  1. Object constraint language, version 2.2. Tech. rep., Object Management Group, OMG (2010). http://www.omg.org/spec/OCL/2.2. OMG Document Number: formal/2010-02-01

  2. Van der Aalst, W., Van Hee, K.: Business process redesign: a Petri-net-based approach. Comput. Ind. 29(1–2), 15–26 (1996)

    Article  Google Scholar 

  3. Aier, S., Fischer, C.: Criteria of progress for information systems design theories. Inf. Syst. E Bus. Manag. 9(1), 133–172 (2011)

    Google Scholar 

  4. Ballou, D.P., Pazer, H.L.: Modeling data and process quality in multi-input, multi-output information systems. Manag. Sci. 31(2), 150–162 (1985). http://www.jstor.org/stable/2631512

  5. Barber, K., Graser, T., Holt, J.: Enabling iterative software architecture derivation using early non-functional property evaluation. In: Proceedings of the 17th IEEE International conference on Automated Software Engineering (ASE), pp. 172–182 (2002)

  6. Batini, C., Scannapieco, M.: Data Quality: Concepts, Methodologies and Techniques. Springer, New York (2006)

    Google Scholar 

  7. Bengtsson, P., Bosch, J.: Scenario-based software architecture reengineering. In: Proceedings of the Fifth International Conference on Software Reuse, 1998, pp. 308–317. IEEE (2002)

  8. Bharadwaj, A., Keil, M., Mähring, M.: Effects of information technology failures on the market value of firms. J. Strateg. Inf. Syst. 18(2), 66–79 (2009)

    Article  Google Scholar 

  9. Bocciarelli, P., D’Ambrogio, A.: A model-driven method for describing and predicting the reliability of composite services. Softw. Syst. Model. 10, 265–280 (2011). doi:10.1007/s10270-010-0150-3

  10. Bradley, R.V., Pratt, R.M.E., Byrd, T.A., Simmons, L.: The role of enterprise architecture in the quest for it value. MIS Q. Exec. 10(2), 73–80 (2011)

  11. Brynjolfsson, E., Hitt, L.: Paradox lost? firm-level evidence on the returns to information systems spending. Manag. Sci. 42(4), pp. 541–558 (1996). http://www.jstor.org/stable/2634387

    Google Scholar 

  12. Buchholz, P.: A class of hierarchical queueing networks and their analysis. Queueing Syst. 15(1), 59–80 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  13. Buckl, S., Ernst, A., Matthes, F., Schweda, C.: An information model for landscape management-discussing temporality aspects. In: Proceedings of the Service-Oriented Computing-ICSOC 2008 Workshops pp. 363–374 (2009)

  14. Buckl, S., Franke, U., Holschke, O., Matthes, F., Schweda, C., Sommestad, T., Ullberg, J.: A pattern-based approach to quantitative enterprise architecture analysis. In: 15th Americas Conference on Information Systems (AMCIS). Association for, Information Systems (2009)

  15. Burton, B., Allega, P.: Hype Cycle for Enterprise Architecture, 2010. GARTNER, vol. G00201646 (2010)

  16. Buschle, M., Ullberg, J., Franke, U., Lagerström, R., Sommestad, T.: A tool for enterprise architecture analysis using the prm formalism. Information Systems Evolution. Lecture Notes in Business Information Processing, vol. 72, pp. 108–121 (2011)

  17. Buzen, J.: Computational algorithms for closed queueing networks with exponential servers. Commun. ACM 16(9), 527–531 (1973)

    Article  MathSciNet  MATH  Google Scholar 

  18. Buzen, J.: Fundamental operational laws of computer system performance. Acta Informatica 7(2), 167–182 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  19. Chang, H.: Intelligent agent’s technology characteristics applied to online auctions’ task: A combined model of TTF and TAM. Technovation 28(9), 564–577 (2008)

    Article  Google Scholar 

  20. Cobb, B.R., Shenoy, P.P.: Inference in hybrid bayesian networks with mixtures of truncated exponentials. Int. J. Approx. Reason. 41(3), 257–286 (2006). doi:10.1016/j.ijar.2005.06.002

    Google Scholar 

  21. Cortellessa, V., Singh, H., Cukic, B.: Early reliability assessment of uml based software models. In: WOSP ’02: Proceedings of the 3rd international workshop on Software and performance, pp. 302–309. ACM, New York, NY, USA (2002). doi:10.1145/584369.584415

  22. Cushing, B.E.: A mathematical approach to the analysis and design of internal control systems. Acc. Rev. 49(1), 24–41 (1974). http://www.jstor.org/stable/244795

  23. Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989). http://www.jstor.org/stable/249008

  24. De Boer, F., Bonsangue, M., Jacob, J., Stam, A., Van der Torre, L.: Enterprise architecture analysis with xml. In: Proceedings of the 38th Annual Hawaii International Conference on System Sciences 2005, HICSS’05, p. 222b. IEEE (2005)

  25. DeLone, W., McLean, E.: Information systems success: the quest for the dependent variable. Inf. Syst. Res. 3(1), 60–95 (1992)

    Google Scholar 

  26. DeLone, W., McLean, E.: The DeLone and McLean model of information systems success: A ten-year update. J. Manag. Inf. Syst. 19(4), 9–30 (2003)

    Google Scholar 

  27. Demathieu, S., Thomas, F., André, C., Gérard, S., Terrier, F.: First experiments using the uml profile for marte. In: 11th IEEE International Symposium on Object Oriented Real-Time Distributed Computing (ISORC), 2008, pp. 50–57. IEEE (2008)

  28. Dishaw, M., Strong, D.: Supporting software maintenance with software engineering tools: A computed task-technology fit analysis. J. Syst. Softw. 44(2), 107–120 (1998)

    Article  Google Scholar 

  29. Dishaw, M., Strong, D.: Extending the technology acceptance model with task-technology fit constructs. Inf. Manag. 36(1), 9–21 (1999)

    Article  Google Scholar 

  30. DoD: Dod architecture framework version 2.0. United States Department of Defense (2009)

  31. Dunsire, K., O’Neill, T., Denford, M., Leaney, J.: The ABACUS architectural approach to computer-based system and enterprise evolution. In: Proceedings of the 12th IEEE International Conference and Workshops on Engineering of Computer-Based Systems, p. 69. IEEE Computer Society (2005)

  32. Ernst, A.: Enterprise architecture management patterns. In: Proceedings of the 15th Conference on Pattern Languages of Programs, p. 7. ACM (2008)

  33. Framework, E.M.: EMF: OCL plugin for the Eclipse Modeling Framework (2011). http://www.eclipse.org/emf/

  34. Frank, U., Heise, D., Kattenstroth, H., Schauer, H.: Designing and utilising business indicator systems within enterprise models-outline of a method. Modellierung betrieblicher Informationssysteme (MobIS, 2008) : November, Saarbrücken. Germany, pp. 89–105 (2008)

  35. Franke, U., Flores, W.R., Johnson, P.: Enterprise architecture dependency analysis using fault trees and bayesian networks. 42nd Annual Simulation Symposium (ANSS) (2009)

  36. Franke, U., Johnson, P., Ericsson, E., Flores, W.R., Zhu, K.: Enterprise architecture analysis using fault trees and MODAF. In: Proceedings of the CAiSE Forum 2009, vol. 453, pp. 61–66 (2009). ISSN: 1613–0073

  37. Friedman, N., Getoor, L., Koller, D., Pfeffer, A.: Learning probabilistic relational models. In: International Joint Conference on Artificial Intelligence, vol. 16, pp. 1300–1309. Citeseer (1999)

  38. Gammelgård, M., Ekstedt, M., Närman, P.: A method for assessing the business value of information system scenarios with an estimated credibility of the result. Int. J. Serv. Technol. Manag. 13(1), 105–133 (2010)

    Article  Google Scholar 

  39. Gilmore, S., Gönczy, L., Koch, N., Mayer, P., Tribastone, M., Varró, D.: Non-functional properties in the model-driven development of service-oriented systems. Softw. Syst. Model. 10, 287–311 (2011). doi:10.1007/s10270-010-0155-y

  40. Glazner, C.: Understanding enterprise behavior using hybrid simulation of enterprise architecture. Ph.D. thesis, Massachusetts Institute of Technology (2009)

  41. Goodhue, D., Thompson, R.: Task-technology fit and individual performance. Mis Q. 19(2), 213–236 (1995)

    Article  Google Scholar 

  42. Gregor, S., Jones, D.: The anatomy of a design theory. J. Assoc. Inf. Syst. 8(5), 312–335 (2007)

    Google Scholar 

  43. Harrison, P., Patel, N.: Performance Modelling of Communication Networks and Computer Architectures. International Computer Science. Addison-Wesley Longman Publishing Co., Inc., Boston (1992)

    Google Scholar 

  44. Henderson, J., Cooprider, J.: Dimensions of I/S planning and design aids: a functional model of CASE technology. Inf. Syst. Res. 1(3), 227 (1990)

    Article  Google Scholar 

  45. Hevner, A., March, S., Park, J., Ram, S.: Design science in information systems research. Mis Q. 28(1), 75–105 (2004)

    Google Scholar 

  46. Hillier, F., Lieberman, G.: Introduction to Operations Research Eighth. McGraw-Hill, Singapore (2005)

    Google Scholar 

  47. Holschke, O., Närman, P., Flores, W., Eriksson, E., Schönherr, M.: Using enterprise architecture models and bayesian belief networks for failure impact analysis. In: Service-Oriented Computing-ICSOC 2008 Workshops, pp. 339–350. Springer (2009)

  48. Høyland, A., Rausand, M.: System Reliability Theory: Models and Statistical Methods. Wiley, New York (1994)

    Google Scholar 

  49. Iacob, M., Jonkers, H.: Quantitative analysis of enterprise architectures. Interoperability of Enterprise Software and Applications pp. 239–252 (2006)

  50. Iacob, M., Jonkers, H.: Quantitative analysis of service-oriented architectures. Int. J. Enterp. Inf. Syst. 3(1), 42–60 (2007)

    Article  Google Scholar 

  51. Iacob, M.E., Jonkers, H.: Analysis of enterprise architectures. Tech. Rep, Telematica Instituut (TI) (2004)

  52. IBM Global Services: Improving systems availability. Tech. Rep, IBM Global Services (1998)

  53. IEC technical committee 57: Iec 61968-1—application integration at electric utilities—system interfaces for distribution management—part 1: Interface architecture and general requirements (2003)

  54. ISO: Iso/iec 9126–2:2003 software engineering—product quality—part 2: External metrics (2003)

  55. IT Governance Institute: Cobit 4.1. ISACA (2007). http://www.isaca.org/Knowledge-Center/cobit/Pages/Downloads.aspx

  56. Jaeger, M.C., Rojec-Goldmann, G., Muhl, G.: Qos aggregation in web service compositions. In: Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service, 2005. EEE’05, pp.181–185 (2005)

  57. Jain, R.: The Art of Computer Systems Performance Analysis : Techniques for Experimental Design, Measurement, Simulation, and Modeling. Wiley, New York (1991)

    MATH  Google Scholar 

  58. Johansson, E., Ekstedt, M., Johnson, P.: Assessment of enterprise information security: the importance of information search cost. In: Proceedings of the 39th Annual Hawaii International Conference on System Sciences, 2006. HICSS’06, pp. 219a–219a (2006)

  59. Johansson, K.: Driftsäkerhet och underhåll. Studentlitteratur, Lund (1997)

    Google Scholar 

  60. Johnson, P., Ekstedt, M.: Enterprise Architecture: Models and Analyses for Information Systems Decision Making. Studentlitteratur, Lund (2007)

    Google Scholar 

  61. Johnson, P., Lagerström, R., Närman, P., Simonsson, M.: Enterprise architecture analysis with extended influence diagrams. Inf. Syst. Front. 9(2), 163–180 (2007)

    Article  Google Scholar 

  62. Kans, M., Ingwald, A.: Analysing it functionality gaps for maintenance management. In: Engineering Asset Lifecycle Management. Proceedings of the 4th World Congress of Engineering Asset Management (WCEAM) 2009. The original pulication is available at http://www.springerlink.com

  63. Kasunic, M.: Measuring systems interoperability: challenges and opportunities. Tech. Rep, DTIC Document (2001)

  64. Kazman, R., Bass, L., Webb, M., Abowd, G.: SAAM: A method for analyzing the properties of software architectures. In: Proceedings of the 16th International Conference on Software Engineering, pp. 81–90 (1994)

  65. Kazman, R., Klein, M., Barbacci, M., Longstaff, T., Lipson, H., Carriere, J.: The architecture tradeoff analysis method. In: Proceedings of the Fourth IEEE International Conference on Engineering of Complex Computer Systems, 1998. ICECCS’98, pp. 68–78 (2002)

  66. Klein, M., Kazman, R., Bass, L., Carriere, J., Barbacci, M., Lipson, H.: Attribute-based architecture styles. In: Software Architecture: TC2 First Working IFIP Conference on Software Architecture (WICSA1): 22–24 February 1999, San Antonio, Texas, USA, p. 225. Kluwer Academic Publishing, Dordrecht (1999)

  67. Klopping, I., McKinney, E.: Extending the technology acceptance model and the task and the task-technology fit model to technology fit model to consumer E Consumer E-Commerce. Inf. Technol. Learn. Perform. J. 22(1), 35 (2004)

    Google Scholar 

  68. Kurpjuweit, S., Winter, R.: Viewpoint-based meta model engineering. EMISA 2007, 143 (2007)

    Google Scholar 

  69. Lagerström, R., Johnson, P., Höök, D.: Architecture analysis of enterprise systems modifiability-models, analysis, and validation. J. Syst. Softw. 83(8), 1387–1403 (2010)

    Article  Google Scholar 

  70. Lam, S., Lien, Y.: A tree convolution algorithm for the solution of queueing networks. Commun. ACM 26(3), 215 (1983)

    Article  Google Scholar 

  71. Lankhorst, M.: Enterprise Architecture at Work: Modelling, Communication and Analysis. Springer, Berlin (2009)

    Book  Google Scholar 

  72. Lankhorst, M., Proper, H., Jonkers, H.: The Architecture of the ArchiMate Language. In: Enterprise, Business-Process and Information Systems Modeling: 10th International Workshop, Bpmds 2009, and 14th International Conference, Emmsad 2009, Held at Caise 2009, Amsterdam, the Netherlands, June 8–9, 2009, Proceedings, p. 367. Springer (2009)

  73. Laprie, J., Kanoun, K.: X-ware reliability and availability modeling. IEEE Trans. Softw. Eng. 18(2), 130–147 (2002)

    Article  Google Scholar 

  74. Leangsuksun, C., Shen, L., Liu, T., Song, H., Scott, S.: Availability prediction and modeling of high mobility OSCAR cluster. In: Proceedings of the 2003 IEEE International Conference on Cluster Computing, 2003, pp. 380–386. IEEE (2005)

  75. Ledoux, J.: Availability modeling of modular software. IEEE Trans. Reliab. 48(2), 159–168 (2002)

    Article  Google Scholar 

  76. Lee, Y.W., Pipino, L.L., Funk, J.D., Wang, R.Y.: Journey to Data Quality. MIT Press, Cambridge (2006)

    Google Scholar 

  77. Lankhorst, M.M.: Enterprise architecture modelling-the issue of integration. Adv. Eng. Inform. 18(4), 205–216 (2004). doi:10.1016/j.aei.2005.01.005

  78. March, S.T., Smith, G.F.: Design and natural science research on information technology. Decis. Support Syst. 15(4), 251–266 (1995). doi:10.1016/0167-9236(94)00041-2

  79. Melville, N., Kraemer, K., Gurbaxani, V.: Review: information technology and organizational performance: An integrative model of it business value. MIS Q. 28(2), pp. 283–322 (2004). http://www.jstor.org/stable/25148636

  80. de Miguel, M., Lambolais, T., Hannouz, M., Betgé-Brezetz, S., Piekarec, S.: UML extensions for the specification and evaluation of latency constraints in architectural models. In: Proceedings of the 2nd international workshop on Software and performance, pp. 83–88. ACM (2000)

  81. Ministry of Defence: MODAF Handbook, technical specification for MODAF. Ministry of Defence (2005)

  82. Montgomery, D.: Design and Analysis of Experiments. Wiley, New York (1991)

    MATH  Google Scholar 

  83. Mukhopadhyay, T., Kekre, S., Kalathur, S.: Business value of information technology: A study of electronic data interchange. MIS Q. 19(2), pp. 137–156 (1995). http://www.jstor.org/stable/249685

  84. Närman, P., Buschle, M., König, J., Johnson, P.: Hybrid probabilistic relational models for system quality analysis. In: Enterprise Distributed Object Computing Conference 2010, EDOC ’10: Vitoria, ES, Brazil. 14th International IEEE. IEEE (2010) (inpress)

  85. Närman, P., Holm, H., Ekstedt, M., Honeth, N.: An interview-based enterprise architecture analysis method for service response time predictions. J. Strateg. Inf. Syst. (2011) (submitted)

  86. Närman, P., Holm, H., Höök, D., Honeth, N., Johnson, P.: Using enterprise architecture and technology adoption models to predict application usage. J. Syst. Softw. 85(8), 1953–1967 (2012)

    Google Scholar 

  87. Närman, P., Holm, H., Johnson, P., König, J., Chenine, M., Ekstedt, M.: Data accuracy assessment using enterprise architecture. Enterp. Inf. Syst. 5(1), 37–58 (2011)

    Article  Google Scholar 

  88. Närman, P., Johnson, P., Lagerström, R., Franke, U., Ekstedt, M.: Data collection prioritization for system quality analysis. Electron. Notes Theor. Comput. Sci. 233, 29–42 (2009)

    Article  Google Scholar 

  89. NATO Consultation, Command and Control Board: Command and control board (nc3b):“Snato c3 system architecture framework. Tech. Rep., AC/322-WP/0125, Brussels (2007)

  90. Närman, P., Franke, U., König, J., Buschle, M., Ekstedt, M.: Enterprise architecture availability analysis using fault trees and stakeholder interviews. Enterp. Inf. Syst. 0(0), 1–25 (2012). doi:10.1080/17517575.2011.647092. Available online 31 Jan 2012

  91. Nunamaker, J., Chen, M., Purdin, T.: Systems development in information systems research. J. Manag. Inf. Syst. 7(3), 89–106 (1990)

    Google Scholar 

  92. Pagani, M.: Determinants of adoption of high speed data services in the business market: Evidence for a combined technology acceptance model with task technology fit model. Inf. Manag. 43(7), 847–860 (2006). doi:10.1016/j.im.2006.08.003

  93. Palmer, J.: Web site usability, design, and performance metrics. Inf. Syst. Res. 13(2), 151–167 (2003)

    Article  Google Scholar 

  94. Patton, J.D.: Preventive maintenance. Instrument Society of America, New York (1983)

  95. Bernus, P.: Enterprise models for enterprise architecture and iso9000:2000. Annu. Rev. Control 27(2), 211–220 (2003). doi:10.1016/j.arcontrol.2003.09.004

  96. Petriu, D., Wang, X.: From UML descriptions of high-level software architectures to LQN performance models. In: Applications of Graph Transformations with Industrial Relevance, Lecture Notes in Computer Science, vol. 1779/2000, pp. 217–221 (2000). doi:10.1007/3-540-45104-8_4

  97. Raderius, J., Närman, P., Ekstedt, M.: Assessing system availability using an enterprise architecture analysis approach. In: Proceedings of 3rd Workshop on Trends in Enterprise Architecture Research (TEAR 2008), Sydney, Australia. Springer (2009)

  98. Redman, T.C.: Data Quality for the Information Age. Artech House, Boston (1996)

    Google Scholar 

  99. Redman, T.C.: The impact of poor data quality on the typical enterprise. Commun. ACM 41, 79–82 (1998). doi:10.1145/269012.269025

  100. Reiser, M., Lavenberg, S.: Mean-value analysis of closed multichain queuing networks. J. ACM (JACM) 27(2), 313–322 (1980)

    Article  MathSciNet  MATH  Google Scholar 

  101. Reussner, R., Schmidt, H., Poernomo, I.: Reliability prediction for component-based software architectures. J. Syst. Softw. 66(3), 241–252 (2003)

    Article  Google Scholar 

  102. Riempp, G., Gieffers-Ankel, S.: Application portfolio management: a decision-oriented view of enterprise architecture. Inf. Syst. E Bus. Manag. 5(4), 359–378 (2007)

    Article  Google Scholar 

  103. Rodrigues, G., Rosenblum, D., Uchitel, S.: Using scenarios to predict the reliability of concurrent component-based software systems. Lecture Notes in Computer Science, vol. 3442, pp. 111–126 (2005). doi:10.1007/978-3-540-31984-9_9

  104. Ross, J., Beath, C.: Sustainable it outsourcing success: Let enterprise architecture be your guide. MIS Q. Exec. 5(4), 8–92 (2006)

    Google Scholar 

  105. Ross, J., Weill, P., Robertson, D.: Enterprise Architecture as Strategy: Creating a Foundation for Business Execution. Harvard Business Press, Boston (2006)

    Google Scholar 

  106. Sasa, A., Krisper, M.: Enterprise architecture patterns for business process support analysis. J. Syst. Softw. 84(9): 1480–1506 (2011)

    Google Scholar 

  107. Scott, D.: How to Assess Your IT Service Availability Levels (2009)

  108. Simon, D., Fischbach, K., Schoder, D.: Application portfolio management-an integrated framework and a software tool evaluation approach. Comm. Assoc. Inf. Syst. 26(1), 3 (2010)

    Google Scholar 

  109. Smit, K., Slaterus, W.: Information Model for Maintenance Management (IMMM). Cap Gemini Publishing, Rijswijk (1922)

    Google Scholar 

  110. Smith, C., Williams, L.: Performance Solutions: A Practical Guide to Creating Responsive, Scalable Software. Addison-Wesley, Boston (2002)

  111. Sommestad, T., Ekstedt, M., Johnson, P.: A probabilistic relational model for security risk analysis. Comput. Secur (2010)

  112. Stamatelatos, M., Vesely, W., Dugan, J., Fragola, J., Minarick, J., Railsback, J.: Fault tree handbook with aerospace applications (2002). http://www.hq.nasa.gov/office/codeq/doctree/fthb.pdf

  113. International Organization for Standardization.: Iso/iec 42010:2007—systems and software engineering—recommended practice for architectural description of software-intensive systems. JTC 1/SC 7—Softw. Syst. Eng. (2007)

  114. The Open Group: Archimate 1.0 specification. Van Haren Publishing, Zaltbommel (2009)

  115. The Open Group: Togaf version 9 “enterprise edition” (2009)

  116. Ullberg, J., Franke, U., Buschle, M., Johnson, P.: A tool for interoperability analysis of enterprise architecture models using pi-OCL. In: Proceedings of the International Conference on Interoperability for Enterprise Software and Applications (I-ESA) (2010)

  117. Ullberg, J., Lagerström, R., Johnson, P.: A framework for service interoperability analysis using enterprise architecture models. In: IEEE International Conference on Services Computing (2008)

  118. Van Bon, J.: Foundations of IT Service Management based on ITIL. Van Haren Publishing, Zaltbommel (2007)

  119. Venkatesh, V., Bala, H., Venkatraman, S., Bates, J.: Enterprise architecture maturity: The story of the veterans health administration. MIS Q. Exec. 6(2), 79–90 (2007)

    Google Scholar 

  120. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: Toward a unified view. MIS Q. 27(3), pp. 425–478 (2003). http://www.jstor.org/stable/30036540

  121. Venkatraman, N.: The concept of fit in strategy research: Toward verbal and statistical correspondence. Acad. Manag. Rev. 14(3), 423–444 (1989)

    Google Scholar 

  122. Vessey, I.: Expertise in debugging computer programs: An analysis of the content of verbal protocols. Systems, Man and Cybernetics, IEEE Transactions on 16(5), 621–637 (1986). doi:10.1109/TSMC.1986.289308

    Article  Google Scholar 

  123. Walls, J., Widmeyer, G., El Sawy, O.: Building an information system design theory for vigilant eis. Inf. Syst. Res. 3(1), 36–59 (1992)

    Article  Google Scholar 

  124. Wang, R., Ziad, M., Lee, Y.: Data Quality. Kluwer Academic Publishing, Dordrecht (2001)

    MATH  Google Scholar 

  125. Wang, R.Y.: Information Quality. M. E. Sharpe, Armonk (2005)

    Google Scholar 

  126. Wang, W., Wu, Y., Chen, M.: An architecture-based software reliability model. In: Dependable Computing, 1999. Proceedings. 1999 Pacific Rim International Symposium on, pp. 143–150. IEEE (2002)

  127. Wang, W.L., Pan, D., Chen, M.H.: Architecture-based software reliability modeling. J. Syst. Softw. 79(1), 132–146 (2006). doi:10.1016/j.jss.2005.09.004

    Google Scholar 

  128. Weill, P., Vitale, M.: Assessing the health of an information systems applications portfolio: An example from process manufacturing. MIS Q. 23(4), 601–624 (1999)

    Article  Google Scholar 

  129. Woodhouse, J.: Putting the total jigsaw puzzle together: PAS 55 standard for the integrated, optimized management of assets. In: International Maintenance Conference (2006)

  130. Yacoub, S., Cukic, B., Ammar, H.: A scenario-based reliability analysis approach for component-based software. Reliability, IEEE Transactions on 53(4), 465–480 (2004). doi:10.1109/TR.2004.838034

    Article  Google Scholar 

  131. Zachman, J.: A framework for information systems architecture. IBM Syst. J. 38(2/3), 454–470 (1999)

    Article  Google Scholar 

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Authors and Affiliations

  1. Royal Institute of Technology, Industrial Information and Control Systems, Osquldas väg 10, 10044 , Stockholm, Sweden

    Per Närman, Markus Buschle & Mathias Ekstedt

Authors
  1. Per Närman
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  2. Markus Buschle
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  3. Mathias Ekstedt
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Corresponding author

Correspondence to Per Närman.

Additional information

Communicated by Dr. Tony Clark, Balbir Barn, Alan Brown, and Florian Matthes.

Appendices

Appendix A: p-OCL statements

Below are the attribute definitions and operations employed for this paper. In Figs. 3, 6, 8 and 10, we have omitted the role labels on the relations to avoid cluttering the figures to much. In the p-OCL statements below, it is assumed that the ‘main direction role’ gets the same name as the relation name, but with a small case letter. The other role has the same name, but with the added ‘_inv’ at the end.

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Appendix B: OCL code for metamodel invariants

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Appendix C: Instructions for using the EAAT tool

In order to comprehend the models that are presented in the submission you need to use the enterprise architecture analysis tool. The following describes the usage with a Windows operating system:

  1. 1.

    Download the file “SoSyM-GUPM.zip” from http://www.ics.kth.se/eat/SoSyMGUPM.zip.

  2. 2.

    Extract the zip file “SoSyMGUPM.zip”.

  3. 3.

    In the created folder you find two subfolders (CM containing the tool and Model containing the presented model).

  4. 4.

    If you are using Windows with limited user privileges, please copy the jsmile.dll to be found in the CM folder into your C:\windows\system32 folder (you must have administrator privileges to do so).

  5. 5.

    Execute the runCM.bat file that is included in the CM folder.

  6. 6.

    In the “Load Abstract Model File/ previously created Model” dialog that is shown on start click on the browse button and navigate to the Model folder, which was included in the zip file. Select “EntireGUPMShowcase.iEaat” and press the ok button.

  7. 7.

    Now the Enterprise Architecture Analysis Tool is shown allowing to consider both models and meta model used within the paper.

  8. 8.

    To the left you find “Views” that correspond to the viewpoints presented in Sect. 5 of the submission.

  9. 9.

    Below you find the “Meta model” and the “Viewpoints” as they have been described in Sects. 4 and 5.

  10. 10.

    Right-clicking on entities of the models shows details and allows to trace how attribute values are calculated.

  11. 11.

    The models can be calculated by clicking the “Calculate” button at the upper right-side of the tool.

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Närman, P., Buschle, M. & Ekstedt, M. An enterprise architecture framework for multi-attribute information systems analysis. Softw Syst Model 13, 1085–1116 (2014). https://doi.org/10.1007/s10270-012-0288-2

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  • DOI: https://doi.org/10.1007/s10270-012-0288-2

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