Skip to main content
SpringerLink
Log in

Towards a Methodology for Knowledge Reuse Based on Semantic Repositories

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

Although reuse is generally considered a good practice within software engineering, several problems dissuade its industrial application and a new viewpoint is needed. This paper presents a new perspective of reuse based on improved retrieval techniques for semantic content (knowledge). This approach, called Universal Knowledge Reuse Methodology (UKRM), drops the investment costs needed in systematic reuse, including the cost of traceability in the process, and reduces the chaos of ad-hoc reuse. UKRM makes reuse independent of the type of content, the context where it will be reused, and even the user that demands it. The paper includes an incremental experiment in order to validate the feasibility of this proposal.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22

Similar content being viewed by others

Notes

  1. Some examples: http://souceforge.net, http://www.codeproject.com, http://www.codeplex.com/, http://www.google.com/codesearch, http://www.planet-source-code.com/, http://www.tucows.com/

References

  • Abecker, A., Bernardi, A., Hinkelmann, K., Kuhn, O., & Sintek, M. (1998). Towards a technology for organisational memories. IEEE Intelligent Systems, 13(3), 30–34.

    Article  Google Scholar 

  • Ackoff, R. L. (1989). From data to wisdom. Journal of Applied Systems Analysis, 16, 3–9.

    Google Scholar 

  • Antunes, B., Seco, N., & Gomes, P. (2007). Using ontologies for software development knowledge reuse. In: Neves J., Santos M.F., Machado J.M. (eds) Progress in Artificial Intelligence. EPIA 2007. Lecture Notes in Computer Science, 4874. Springer, Berlin, Heidelberg

  • Baeza-Yates, R. A., & Ribeiro-Neto, B. (1999). Modern information retrieval. Addison Wesley Longman Limited Publishing Co., Inc., Boston, MA

  • Baxter, D., Gao, J., Case, K., Harding, J., Young, B., Cochrane, S., & Dani, S. (2007). An engineering design knowledge reuse methodology using process modelling. Research in Engineering Design, 18(1), 37–48.

    Article  Google Scholar 

  • Baxter, D., Gao, J., & Roy, R. (2008). Design process knowledge reuse challenges and issues. Computer-Aided Design and Applications, 5(6), 942–952.

    Article  Google Scholar 

  • Bechofer, S., & Goble, C. (2001). Thesaurus construction through knowledge representation. Data & Knowledge Engineering, 37, 25–45.

    Article  Google Scholar 

  • Bellinger, G., Castro, D., & Mills, A. (2004). Data, information, knowledge, and wisdom. http://www.systems-thinking.org/dikw/dikw.htm.

  • Brachman, R. J. (1983). What IS-A is and isn't. And analysis of taxonomic links in semantic networks. Computer, 16(10), 30–36.

  • Brayton, G.N. (1983). Simplified method of measuring productivity identifies opportunities for increasing it. Industrial Engineering. (February): pp. 49-56.

  • Buckingham Shum, S. (1998). Negotiating the construction of organisational memories. In U. M. Borghoff & R. Pareschi (Eds.), Information Technology for Knowledge Management (pp. 55–78). Berlin: Springer.

    Chapter  Google Scholar 

  • Buckley, C., & Voorhees, E. M. (2005). Retrieval system evaluation. In TREC: Experiment and evaluation in information retrieval (pp. 53–75). Cambridge: MIT Press.

  • Chalé-Góngora, G., Llorens, J. Gallego, E. (2017). Your wish, my command – Speeding up projects in the transportation industry using ontologies. INCOSE international symposium. Session 7 track 5. Transportation.

  • Chitnis M., Tiwari P., Ananthamurthy L. (2003). UML Tools. http://www.developer.com/article.php/1593811

  • Davenport, T., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Boston Massachusetts: Harvard Business School Press.

    Google Scholar 

  • Davis, R., Shrobe, H., & Szolovits, P. (1993). What is a knowledge representation? AI Magazine, 14(1), 17–33.

    Google Scholar 

  • Demian, P., Fruchter, R. (2001). CoMem: Knowledge reuse from a corporate memory. Stanford University Thesis.

  • Dretske, F. I. (1981). Knowledge and the flow of information. Cambridge: The MIT Press/Bradford. Books.

    Google Scholar 

  • Dutton E. S. (1997). Effects of knowledge reuse on the spacecraft development process. Master's thesis, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, June 1997.

  • Esteban J. (2007). Survey of model-based systems engineering (MBSE) methodologies. Jet propulsionlaboratory, California Institute of Technology, Pasedena, CA.

  • Exman, I., Llorens, J., Fraga, A. (2015). Jose María Álvarez Rodríguez: SKYWare: The Unavoidable Convergence of Software towards Runnable Knowledge. J. UCS 21(11), 1405–1424.

  • Floridi, L. (2005). Is semantic information meaningful data? Philosophy and Phenomenological Research, 70(2), 351–370.

    Article  Google Scholar 

  • Fowler, J. (2003). UML Distilled: A brief guide to the standard object modeling language. Addison-Wesley professional. 3rd edition. ISBN-13: 978-0321193681.

  • Fraga, Anabel. (2010). Universal knowledge reuse methodology. PhD Dissertation in the Carlos III of Madrid University.

  • Fraga, A. (2015). Quality of requirements in the industrial environment. Software Knowledge Workshop. IC3K Conference.

  • Fraga, A. (2016). Systems engineering in the industrial environment: Requirements engineering processes. Software Knowledge Workshop. IC3K Conference.

  • Fraga, A. (2017) Extraction of patterns using NLP: Genetic deafness. SEKE, 428–431.

  • Frakes, W., & Kang, K. (2005). Software reuse research: Status and future. IEEE Transactions on Software Engineering, 31(7), 529–536.

    Article  Google Scholar 

  • Frakes, W., Prieto-Diaz, R., & Fox, C. (1998). DARE: Domain analysis and reuse environment. Annals of Software Engineering, 5(1998), 125–141.

    Article  Google Scholar 

  • Gallego, E. et al. (2016) Requirements quality analysis: A successful case study in the industry. CSDM, 187–201.

  • Gettier, E. (1983). Is justified true belief knowledge? Analysis, 23, 121–123.

    Article  Google Scholar 

  • Hill et al. (2002). Integration of Knowledge Organization Systems into Digital Library Architectures. ASIST SigCR - http://www.lub.lu.se/SEMKOS/docs/Hill_KOSpaper7-2-final.doc. Last visited on 15th of November of 2007.

  • Hofkirchner, W. (1999). Towards a unified theory of information. The merging of second-order cybernetics and semiotics into a single and comprehensive information science. In: 15e Congrès International de Cybernétique, Namur 1998, Namur, pp. 175–180.

  • Hummel, O., Janjic, W., Atkinson, C. Code conjurer: Pulling reusable software out of thin air. IEEE Software. September/October 2008.

  • Janée G., Ikeda S., Hill L. (2002). ADL Thesaurus Protocol v1.0. http://www.alexandria.ucsb.edu/thesaurus/protocol http://nkos.slis.kent.edu/2002workshop/janee.ppt. Last visited on 15th of November of 2007.

  • Jorgenson, D. W., & Griliches, Z. (1967). The explanation of productivity change. Review of Economic Studies, 34(99), 249–283.

    Article  Google Scholar 

  • Karlsson E.-A. (1995). Software reuse: A holistic approach. Even-André Karlsson (Ed.). JohnWiley & Sons, Inc., New York, USA.

  • KRAFT: Knowledge Fusion from Distributed Databases and Knowledge Bases. (2000) http://www.csd.abdn.ac.uk/research/kraft.html.

  • Kuhn, O., & Abecker, A. (1997). Corporate memories for knowledge Management in Industrial Practice: Prospects and challenges. Journal of Universal Computer Science, 3(8), 929–954.

    Google Scholar 

  • J. Llorens, J. Morato, G. Genova (2004). RSHP: An information representation model based on relationships.” In E. Damiani, L. C. Jain, M. Madravio (Eds.), Soft Computing in Software Engineering (Studies in Fuzziness and Soft Computing Series, Vol. 159) (pp 221–253). Berlin: Springer. Available for reviewers in ftp://www.ie.inf.uc3m.es/llorens/ICSR.zip

  • Llorens, Juan; Fuentes, José M.; Prieto-Diaz, Rubén; Astudillo, Hernán. 2006. Incremental Software Reuse. International Conference of Software Reuse (ICSR2006). Torino, Italy.

  • Lynne, M. (2001). Toward a Theory of Knowledge Reuse: Types of Knowledge Reuse Situations and factors in Reuse Success. Journal of Management Information Systems, 18(1), 57–94.

    Article  Google Scholar 

  • Majchrzak, A., Neece, O. E., Cooper, L. P. (2001). Knowledge reuse for innovation – the missing focus in knowledge management. Academy of Management Proceedings. https://doi.org/10.5465/apbpp.2001.6133668

  • Mäki, Eerikki. (2008). Exploring and exploiting knowledge. Research on knowledge processes in knowledge-intensive organizations. Helsinki University of Technology, Department of Industrial Engineering and Management doctoral dissertation series. pp. 182

  • Manning, C., Raghavan, P., & Schütze, H. (2008). Introduction to information retrieval. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Martin, J. N. (1996). Systems engineering guidebook: A process for developing systems and products. Boca Raton: CRC Press, Inc..

    Google Scholar 

  • Merriam Webster Dictionary Online II (2017) Universal Term Definition. http://www.merriam-webster.com/dictionary/universal (Last visited on 15th of January of 2014).

  • Moffat, A., & Zobel, J. (2008). Rank-biased precision for measurement of retrieval effectiveness. ACM Transactions on Information Systems, 27(1), 1–27.

    Article  Google Scholar 

  • Morisio, M., Ezran, M., & Tully, C. (2002). Success and failure factors in software reuse. IEEE Transactions on Software Engineering, 28(4), 340–357.

    Article  Google Scholar 

  • Neighbors, J. M. (1994). "Reuse so far: phasing in a revolution", Software reuse: Advances in Software Reusability. Proceedings. Third International Conference on, pp. 191–192

  • Pérez-Montoro Gutiérrez, M. (2001). La representación y organización del conocimiento : metodologías, modelos y aplicaciones. Actas del V Congreso ISKO-España. Alcalá de Henares, Madrid

  • Pérez-Montoro Gutiérrez, Mario (2004). “Identificación y representación del conocimiento organizacional: la propuesta epistemológica clásica”. Barcelona: IN3-UOC (Discussion Paper Series; DP04–01). 29 págs. <www.uoc.edu/in3/dt/20390/index.html>. (Last visited on September of 2004).

  • Pérez-Montoro Gutiérrez, M. (2007). The Phenomenon of Information. Lanham (Maryland): Scarecrow Press.

    Google Scholar 

  • Pérez-Montoro Gutiérrez, M., & Campos Havidich, M. (2002). Representación y procesamiento del conocimiento. Universitat Oberta de Catalunya.

  • Poulin, J. S., Caruso, J. M., & Hancock, D. R. (1993). The business case for software reuse. IBM Systems Journal, 32(4), 567–594.

    Article  Google Scholar 

  • Salton, G., Fox, E. A., Wu. H. (1983). Extended Bolean Information Retrieval”. Communications of the ACM, 26(11)

  • Sanchez-Cuadrado, S., Morato-Lara, J., Palacios-Madrid, V., Llorens-Morillo, J., & Moreiro-González, J.-A. (2007). De repente, ¿todos hablamos de ontologías? El Profesional de la Información 16(6), 562–568.

  • Sowa, J. F. (2000). Knowledge Representation: Logical, Philosophical, and Computational Foundations. New York: Brooks/Cole.

    Google Scholar 

  • Sturgeon, S., Martin, G. G. F. Crayling, A. C. (1998). “Epistemology”. En Crayling, A. C. (ed.) Philosophy 1 (Capítulo 1, p. 7–26). Oxford: Oxford University Press.

  • Sumanth, D. (1979). Productivity measurement and evaluation models for manufacturing companies (p. 291). Chicago: Illinois Institute of Technology.

    Google Scholar 

  • Turpin, Andrew; Scholer, Falk(2006) User performance versus precision measures for simple search tasks. Proceedings of the 9th Annual international ACM SIGIR Conference on Research and Development in information Retrieval (Seattle, Washington, USA, August 06–11, 2006) (New York, NY: ACM): 11–18. https://doi.org/10.1145/1148170.1148176.

Download references

Author information

Authors and Affiliations

  1. Departamento de Informática, Universidad Carlos III de Madrid, Av. Universidad 30, Leganés, 28911, Madrid, Spain

    Anabel Fraga, Juan Llorens & Gonzalo Génova

Authors
  1. Anabel Fraga
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juan Llorens
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gonzalo Génova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anabel Fraga.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fraga, A., Llorens, J. & Génova, G. Towards a Methodology for Knowledge Reuse Based on Semantic Repositories. Inf Syst Front 21, 5–25 (2019). https://doi.org/10.1007/s10796-018-9862-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-018-9862-7

Keywords

Search

Navigation