Innovations in Knowledge Management pp 179-209

Part of the Intelligent Systems Reference Library book series (ISRL, volume 95) | Cite as

Context-Aware and Process-Centric Knowledge Provisioning: An Example from the Software Development Domain

Chapter

Abstract

With the increasing availability of information and knowledge, effective knowledge utilization is becoming a growing and key competency within organizations in various knowledge-intensive fields. One current challenge in process-oriented work, such as that exhibited in new product development projects, is the provisioning of contextually-relevant knowledge to the knowledge workers at the appropriate point in their process. This chapter provides background on technical challenges, referring to the software engineering domain to exemplify these. Thereafter, a practical solution approach based on the Context-aware Software Engineering Environment Event-driven framework (CoSEEEK) is presented. Subsequently, it is shown how automated knowledge provisioning within processes, contextual adaptation of processes, and collaborative process support can be realized.

Keywords

Context awareness Process awareness Automatic knowledge provisioning Knowledge management Semantic processing 

References

  1. 1.
    Lenz, R., Reichert, M.: IT support for healthcare processes-premises, challenges, perspectives. Data Knowl. Eng. 61(1), 39–58 (2007)CrossRefGoogle Scholar
  2. 2.
    Müller, D., Herbst, J., Hammori, M., Reichert, M.: IT support for release management processes in the automotive industry. In: Proceedings of 4th International Conference on Business Process Management, pp. 368–377 (2006)Google Scholar
  3. 3.
    Mutschler, B., Reichert, M., Bumiller, J.: Unleashing the effectiveness of process-oriented information systems: Problem analysis, critical success factors, and implications. Syst. Man Cybern. Part C Appl. Rev. IEEE Trans. 38(3), 280–291 (2008)CrossRefGoogle Scholar
  4. 4.
    Gibson, D.L., Goldenson, D.R., Kost, K.: Performance results of CMMI-based process improvement. Technical Report, Software Engineering Institute, Carnegie-Mellon University, Pittsburgh (2006)Google Scholar
  5. 5.
    Heravizadeh, M.: Quality-aware business process management. PhD Thesis, Queensland University of Technology (2009)Google Scholar
  6. 6.
    Lohrmann, M., Reichert, M.: Efficacy-aware business process modeling. In: Proceedings of 20th International Conference on Cooperative Information Systems, pp. 38–55 (2012)Google Scholar
  7. 7.
    Lohrmann, M., Reichert, M.: Understanding business process quality. In: Business Process Management, pp. 41–73. Springer, Berlin (2013)Google Scholar
  8. 8.
    Gloet, M., Terziovski, M.: Exploring the relationship between knowledge management practices and innovation performance. J. Manuf. Technol. Manage. 15(5), 402–409 (2004)CrossRefGoogle Scholar
  9. 9.
    Künzle, V., Weber, B., Reichert, M.: Object-aware business processes: Fundamental requirements and their support in existing approaches. Int. J. Inf. Syst. Model. Des. (IJISMD) 2(2), 19–46 (2011)CrossRefGoogle Scholar
  10. 10.
    Mundbrod, N., Kolb, J., Reichert, M.: Towards a system support of collaborative knowledge work. In: Proceedings of Business Process Management Workshops, pp. 31–42 (2013)Google Scholar
  11. 11.
    Ramesh, B., Tiwana, A.: Supporting collaborative process knowledge management in new product development teams. Decis. Support Syst. 27, 213–235 (1999)CrossRefGoogle Scholar
  12. 12.
    Müller, D., Reichert, M., Herbst, J.: A new paradigm for the enactment and dynamic adaptation of data-driven process structures. In: Proceedings 20th International Conference on Advanced Information Systems Engineering, pp. 48–63 (2008)Google Scholar
  13. 13.
    Bonifacio, M., Bouquet, P., Cuel, R.: Knowledge nodes: the building blocks of a distributed approach to knowledge management. J. Univ. Comput. Sci. 8(6), 652–661 (2002)Google Scholar
  14. 14.
    Maier, R.: Knowledge Management Systems: Information and Communication Technologies for Knowledge Management. Springer, New York (2002)CrossRefGoogle Scholar
  15. 15.
    Drucker, P. F.: Knowledge-worker productivity: the biggest challenge. Knowl. Manage. Yearbook 2000–2001 (1999)Google Scholar
  16. 16.
    Davenport, T. H.: Rethinking knowledge work: a strategic approach. McKinsey Q. 1(11), 88–99 (2011)Google Scholar
  17. 17.
    Lindvall, M., Rus, I.: Knowledge management in software engineering. IEEE Softw. 19(3), 26–38 (2002)CrossRefGoogle Scholar
  18. 18.
    Grambow, G., Oberhauser, R., Reichert, M.: User-centric abstraction of workflow logic applied to software engineering processes. In: Proceedings of 1st Workshop on Human-Centric Process-Aware Information Systems, LNBIP112, pp. 307–321 (2012)Google Scholar
  19. 19.
    Grambow, G., Oberhauser, R.: Towards automated context-aware selection of software quality measures. In: Proceedings of 5th International Conference on Software Engineering Advances, pp. 347–352 (2010)Google Scholar
  20. 20.
    Grambow, G., Oberhauser, R., Reichert, M.: Contextual injection of quality measures into software engineering processes. Int. J. Adv. Softw. 4(1–2), 76–99 (2011)Google Scholar
  21. 21.
    Grambow, G., Oberhauser, R., Reichert, M.: Towards dynamic knowledge support in software engineering processes In: Proceedings of 6th International Workshop on Applications of Semantic Technologies (AST’11), held in conjunction with INFORMATIK’11, LNI 192, p. 149 (2011)Google Scholar
  22. 22.
    Grambow, G., Oberhauser, R., Reichert, M.: Knowledge provisioning: a context-sensitive process-oriented approach applied to software engineering environments. In: Proceedings of 7th International Conference on Software and Data Technologies, pp. 506–515 (2012)Google Scholar
  23. 23.
    Grambow, G., Oberhauser, R., Reichert, M.: Towards automatic process-aware coordination in collaborative software engineering. In: Proceedings of 6th International Conference on Software and Data Technologies, pp. 5–14 (2011)Google Scholar
  24. 24.
    Grambow, G., Oberhauser, R., Reichert, M.: Enabling automatic process-aware collaboration support in software engineering projects. In: Selected Papers of the ICSOFT’11 Conference. Communications in Computer and Information Science (CCIS) 303, pp. 73–89 (2012)Google Scholar
  25. 25.
    Grambow, G.: Context-aware Process Management for the Software Engineering Domain. Doctoral Thesis, Ulm University (2015). (to appear)Google Scholar
  26. 26.
    Bjørnson, F.O., Dingsøyr, T.: Knowledge management in software engineering: a systematic review of studied concepts, findings and research methods used. Inf. Softw. Technol. 50(11), 1055–1068 (2008)CrossRefGoogle Scholar
  27. 27.
    Kurniawati, F., Jeffery, R.: The long-term effects of an EPG/ER in a small software organisation. In: Proceedings of Australian Software Engineering Conference, pp. 128–136 (2004)Google Scholar
  28. 28.
    Barros, M.O., Werner, C.M.L., Travassos, G.H.: Supporting risks in software project management. J. Syst. Softw. 70(1–2), 21–35 (2004)CrossRefGoogle Scholar
  29. 29.
    Basili, V., Costa, P., Lindvall, M., Mendonca, M., Seaman, C., Tesoriero, R., Zelkowitz, M.: An experience management system for a software engineering research organization. In: Proceedings of 26th Annual NASA Software Engineering Workshop, pp. 29–35 (2001)Google Scholar
  30. 30.
    Liao, S.: Knowledge management technologies and applications—literature review from 1995 to 2002. Expert Syst. Appl. 25(2), 155–164 (2003)CrossRefGoogle Scholar
  31. 31.
    Daskalantonakis, M.K.: A practical view of software measurement and implementation experiences within Motorola. Softw. Eng. IEEE Trans. 18(11), 998–1010 (1992)CrossRefGoogle Scholar
  32. 32.
    Offen, R.J., Jeffery, R.: Establishing software measurement programs. Softw. IEEE 14(2), 45–53 (1997)CrossRefGoogle Scholar
  33. 33.
    Gopal, A., Krishnan, M.S., Mukhopadhyay, T., Goldenson, D.R.: Measurement programs in software development: determinants of success. Softw. Eng. IEEE Trans. 28(9), 863–875 (2002)CrossRefGoogle Scholar
  34. 34.
    Li, Z., Zhou, Y.: PR-Miner: automatically extracting implicit programming rules and detecting violations in large software code. In: ACM SIGSOFT Software Engineering Notes, vol. 30, pp. 306–315 (2005)Google Scholar
  35. 35.
    Ohira, M., Yokomori, R., Sakai, M., Matsumoto, K., Inoue, K., Torii, K.: Empirical project monitor: a tool for mining multiple project data. In: Proceedings of International Workshop on Mining Software Repositories (2004)Google Scholar
  36. 36.
    Schlesinger, F., Jekutsch, S.: ElectroCodeoGram: an environment for studying programming. TeamEthno-online, vol. 2, pp. 30–31 (2006)Google Scholar
  37. 37.
    Nystrom, N.A., Urbanic, J., Savinell, C.: Understanding productivity through non-intrusive instrumentation and statistical learning. . In: Proceedings of 2nd Workshop on Productivity and Performance in High-End Computing (2005)Google Scholar
  38. 38.
    Jiang, T., Ying, J., Wu, M.: CASDE: An environment for collaborative software development. In: Computer Supported Cooperative Work in Design III, LNCS, 4402, pp. 367–376 (2007)Google Scholar
  39. 39.
    Lewandowski, A., Bourguin, G.: Enhancing support for collaboration in software development environments. In: Computer Supported Cooperative Work in Design III, LNCS, 4402, pp. 160–169 (2007)Google Scholar
  40. 40.
    Cook, C., Churcher, N., Irwin, W.: Towards synchronous collaborative software engineering. In: Proceedings of 11th Asia-Pacific Software Engineering Conference, pp. 230–239 (2004)Google Scholar
  41. 41.
    Hattori, L., Lanza, M.: Syde: a tool for collaborative software development. In: Proceedings of 32nd International Conference on Software Engineering, pp. 235–238 (2010)Google Scholar
  42. 42.
    Weber, S., Emrich, A., Broschart, J., Ras, E., Ünalan, Ö.: Supporting software development teams with a semantic process-and artifactoriented collaboration environment. In: Proceedings of Software Engineering (Workshops), pp. 243–254 (2009)Google Scholar
  43. 43.
    de Lucia, A., Fasano, F., Oliveto, R., Tortora, G.: Fine‐grained management of software artefacts: the ADAMS system. Softw. Pract. Experience 40(11), 1007–1034 (2010)Google Scholar
  44. 44.
    de Oliveira, K.M., Zlot, F., Rocha, A.R., Travassos, G.H., Galotta, C., de Menezes, C.S.: Domain-oriented software development environment. J. Syst. Softw. 72(2), 145–161 (2004)CrossRefGoogle Scholar
  45. 45.
    Maciel, R.S.P., da Silva, B.C., Magalhães, P.F., Rosa, N.S.: An integrated approach for model driven process modeling and enactment. In: Proceedings of Software Engineering, 2009. SBES’09. XXIII Brazilian Symposium on, pp. 104–114 (2009)Google Scholar
  46. 46.
    Aleixo, F.A., Freire, M.A., dos Santos, W.C., Kulesza, U.: Automating the variability management, customization and deployment of software processes: a model-driven approach. In: Enterprise Information Systems, pp. 372–387. Springer, Berlin (2011)Google Scholar
  47. 47.
    Dowson, M.: Consistency maintenance in process sensitive environments. In: Proceedings of Process Sensitive Software Engineering Environments Architectures Workshop (1992)Google Scholar
  48. 48.
    Conradi, R., Fernström, C., Fuggetta, A., Snowdon, R.: Towards a reference framework for process concepts. In: Software Process Technology, pp. 1–17. Springer, Berlin (1992)Google Scholar
  49. 49.
    Reichert, M., Weber, B.: Enabling Flexibility in Process-aware Information Systems—Challenges, Methods, Technologies. Springer, Berlin (2012)MATHCrossRefGoogle Scholar
  50. 50.
    Reichert, M., Rinderle-Ma, S., Dadam, P.: Flexibility in process-aware information systems. In: Transactions on Petri Nets and Other Models of Concurrency II, pp. 115–135 (2009)Google Scholar
  51. 51.
    Gelernter, D.: Generative communication in Linda. ACM Trans. Program. Lang. Syst. (TOPLAS) 7(1), 80–112 (1985)MATHCrossRefGoogle Scholar
  52. 52.
    Meier, W.: eXist: an open source native XML database. In: Web, Web-Services, and Database Systems, LNCS, 2593, pp. 169–183 (2009)Google Scholar
  53. 53.
    Johnson, P.M.: Requirement and design trade-offs in Hackystat: an in-process software engineering measurement and analysis system. In: Proceedings of 1st International Symposium on Empirical Software Engineering and Measurement, pp. 81–90 (2007)Google Scholar
  54. 54.
    Luckham, D.C.: The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems. Addison-Wesley Longman Publishing Co., Inc., Boston (2001)Google Scholar
  55. 55.
    Esper. Website: http://esper.codehaus.org. Visited: September (2013)
  56. 56.
    Bellifemine, F., Poggi, A., Rimassa, G.: JADE–A FIPA-compliant agent framework. In: Proceedings of 4th International Conference and Exhibition on the Practical Application of Intelligent Agents and Multi-Agents, pp. 97–108 (1999)Google Scholar
  57. 57.
    Browne, P.: JBoss Drools Business Rules. Packt Publishing, Birmingham (2009)Google Scholar
  58. 58.
    Dadam, P., Reichert, M.: The ADEPT project: a decade of research and development for robust and flexible process support. Comput. Sci. Res. Develop. 23(2), 81–97 (2009)CrossRefGoogle Scholar
  59. 59.
    Lanz, A., Reichert, M., Dadam, P.: Robust and flexible error handling in the AristaFlow BPM Suite. In: Proceedings of CAiSE’10 Forum, Information Systems Evolution, pp. 174–189 (2011)Google Scholar
  60. 60.
    Krötzsch, M., Vrandecic, D., Völkel, M.: Semantic mediawiki. In: Proceedings of International Semantic Web Conference, pp. 935–942 (2006)Google Scholar
  61. 61.
    World Wide Web Consortium: OWL Web Ontology Language Semantics and Abstract Syntax (2004)Google Scholar
  62. 62.
    Sirin, E., Parsia, B., Grau, B.C., Kalyanpur, A., Katz, Y.: Pellet: a practical owl-dl reasoner. Web Semant. Sci. Serv. Agents World Wide Web 5(2), 51–53 (2007)CrossRefGoogle Scholar
  63. 63.
    McBride, B.: Jena: a semantic web toolkit. Internet Comput. IEEE 6(6), 55–59 (2002)CrossRefGoogle Scholar
  64. 64.
    Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M.: SWRL: a semantic web rule language combining OWL and RuleML. W3C Member Submission 21, 79 (2004)Google Scholar
  65. 65.
    Prud’hommeaux, E., Seaborne, A.: SPARQL query language for RDF. W3C WD 4 (2006)Google Scholar
  66. 66.
    Kess, P., Haapasalo, H.: Knowledge creation through a project review process in software production. Int. J. Prod. Econ. 80(1), 49–55 (2002)CrossRefGoogle Scholar
  67. 67.
    Teigland, R., Fey, C.F., Birkinshaw, J.: Knowledge dissemination in global R&D operations: an empirical study of multinationals in the high technology electronics industry. In: MIR: Management International Review, pp. 49–77 (2000)Google Scholar
  68. 68.
    Schaffert, S., Bry, F., Baumeister, J., Kiesel, M.: Semantic wikis. IEEE Softw. 25(4), 8–11 (2008)CrossRefGoogle Scholar
  69. 69.
    Kroll, P., MacIsaac, B.: Agility and Discipline Made Easy: Practices from OpenUP and RUP. Pearson Education, New York (2006)Google Scholar
  70. 70.
    Basili, V.R., Caldiera, V.R.B.G., Rombach, H.D.: The goal question metric approach. Encycl. Softw. Eng. 2, 528–532 (1994)Google Scholar
  71. 71.
    Davenport, T. H., Pruzak, L.: Working Knowledge: How Organizations Manage What They Know. Harvard Business Press, Boston (2000)Google Scholar
  72. 72.
    Alavi, M., Leidner, D. E.: Review: knowledge management and knowledge management systems: conceptual foundations and research issues. MIS Q. 107–136 (2001)Google Scholar
  73. 73.
    Davenport, T.H., David, W., Beers, M.C.: Successful knowledge management projects. Sloan Manage. Rev. 39(2), 43–57 (1998)Google Scholar

Additional Resources on Related Topics: Books

  1. 74.
    Tiwana, A.: The Knowledge Management Toolkit: Practical Techniques for Building a Knowledge Management System. Prentice Hall PTR, New Jersey (2000)Google Scholar
  2. 75.
    Davenport, T.H., Probst, G.J.: Knowledge Management Case Book: Siemens Best Practices. Wiley, New York (2002)Google Scholar
  3. 76.
    Liebowitz, J.: Knowledge Management: Handbook. CRC Press, Boca Raton (1999)Google Scholar
  4. 77.
    Dalkir, K.: Knowledge Management in Theory and Practice. Routledge, London (2013)Google Scholar
  5. 78.
    Ruggles, R.: Knowledge Management Tools. Routledge, London (2012)Google Scholar

Articles

  1. 79.
    Davenport, T.H., David, W., Beers, M.C.: Successful knowledge management projects. Sloan Manage. Rev. 39(2), 43–57 (1998)Google Scholar
  2. 80.
    Alavi, M., Leidner, D.E.: Review: knowledge management and knowledge management systems: conceptual foundations and research issues. MIS Q. 107–136 (2001)Google Scholar
  3. 81.
    IEEE Transactions on Knowledge and Data EngineeringGoogle Scholar

Conferences and Workshops

  1. 82.
    IEEE International Conference on Information Reuse and Integration (IRI)Google Scholar
  2. 83.
    International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K)Google Scholar
  3. 84.
    International Conference on Intelligent Systems and Knowledge Engineering (ISKE)Google Scholar
  4. 85.
    International Workshop on Knowledge Acquisition, Reuse and Evaluation (KARE)Google Scholar
  5. 86.
    Workshop on Knowledge Engineering and Software Engineering (KESE)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Gregor Grambow
    • 1
  • Roy Oberhauser
    • 2
  • Manfred Reichert
    • 1
  1. 1.Institute for Databases and Information SystemsUlm UniversityUlmGermany
  2. 2.Computer Science DepartmentAalen UniversityAalenGermany

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