Skip to main content
SpringerLink
Log in

A Methodology for Developing High Quality Ontologies for Knowledge Management

  • Chapter
  • First Online:
Knowledge Management for Development

Part of the book series: Integrated Series in Information Systems ((ISIS,volume 35))

  • 1032 Accesses

Abstract

Ontologies have been identified as important components of Knowledge Management Systems (KMS), and the quality of such systems is therefore likely to be heavily dependent on the quality of the embedded ontology. This chapter describes an approach to the development, representation, and evaluation of formal ontologies with the explicit aim being to develop a set of techniques that will improve the coverage of the ontology, and thus its overall quality. This will ensure that when the ontology is integrated into the KMS it will not jeopardize the quality of the system as a whole. The proposed approach will be illustrated by applying it to the development and evaluation of an ontology that can be used as a component of a KMS for the information technology (IT) infrastructure at a university campus.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alavi, M., & Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues [Article]. MIS Quarterly, 25(1), 107.

    Article  Google Scholar 

  • Bhatia, S., & Yao, Q. (1993). A new approach to knowledge acquisition by repertory grids. Paper presented at the second international conference on information and knowledge management, Washington, DC.

    Google Scholar 

  • Burton-Jones, A., Storey, V. C., Sugumaran, V., & Ahluwalia, P. (2005). A semiotic metrics suite for assessing the quality of ontologies. Data & Knowledge Engineering, 55, 84–102.

    Article  Google Scholar 

  • Chen, C.-H., Khoo, L. P., & Yan, W. (2002). A strategy for acquiring customer requirement patterns using laddering technique and ART2 neural network. Advanced Engineering Informatics, 16(3), 229–240.

    Article  Google Scholar 

  • Cooke, N. J. (1999). Knowledge elicitation. In F. T. Durso (Ed.), Handbook of applied cognition (pp. 479–509). Chichester: Wiley.

    Google Scholar 

  • Curran, M., Rugg, G., & Corr, S. (2005). Attitudes to expert systems: A card sort study. The Foot, 15, 190–197.

    Article  Google Scholar 

  • Fensel, D., van Harmelen, F., Universiteit, V., Horrocks, I., McGuinness, D., & Patel-Schneider, P. (2001). OIL: An ontology infrastructure for the semantic web. IEEE Intelligent Systems, 16(2), 38–45.

    Article  Google Scholar 

  • Fox, M. S., Barbuceanu, M., Gruninger, M., & Lin, J. (1998). An organization ontology for enterprise modeling. In M. Prietula, K. Carley, & L. Gasser (Eds.), Simulating organizations: Computational models of institutions and groups (pp. 131–152). Menlo Park, CA: AAAI/MIT Press.

    Google Scholar 

  • Fox, M. S., & Gruninger, M. (1998). Enterprise modelling. AI Magazine, 19(3), 109–121.

    Google Scholar 

  • Gangemi, A. (2005). Ontology design patterns for semantic web content. Paper presented at the 4th international semantic web conference (ISWC 2005), Galway, Ireland.

    Google Scholar 

  • Gruninger, M., & Fox, M. S. (1994). The design and evaluation of ontologies for enterprise engineering. Paper presented at the workshop on implemented ontologies, European conference on artificial intelligence (ECAI), Amsterdam, NL.

    Google Scholar 

  • Gruninger, M., & Fox, M. S. (1995). Methodology for the design and evaluation of ontologies. Paper presented at the IJCAI ‘95, workshop on basic ontological issues in knowledge sharing, Montreal, QC, Canada.

    Google Scholar 

  • Guarino, N. (1998). Formal ontology and information systems. Paper presented at the first internation conference on formal ontologies in information systems, Trento, Italy.

    Google Scholar 

  • Guarino, N., Carrara, M., & Giaretta, P. (1994). An ontology of meta-level categories. Paper presented at the fourth international conference on principles of knowledge representation and reasoning (KR ‘94), Bonn, Germany.

    Google Scholar 

  • Guenzi, P., & Troilo, G. (2006). Developing marketing capabilities for customer value creation through marketing–sales integration. Industrial Marketing Management, 35, 974–988.

    Article  Google Scholar 

  • Harper, M. E., Jentsch, F. G., Berry, D., Lau, H. C., Bowers, C., & Salas, E. (2003). TPL–KATS-card sort: A tool for assessing structural knowledge. Behavior Research Methods, Instruments, & Computers, 35(4), 577–584.

    Article  Google Scholar 

  • Hassenzahl, M., & Trautmann, T. (2001). Analysis of web sites with the repertory grid technique. Paper presented at the human factors in computing systems, Seattle, WA.

    Google Scholar 

  • Hickey, A. M., & Davis, A. M. (2003). Elicitation technique selection: How do experts do it? Paper presented at the requirements engineering conference, Monterey Bay, CA.

    Google Scholar 

  • Hölscher, C., & Strube, G. (2000). Web search behavior of internet experts and newbies. Computer Networks, 33(1–6), 337–346.

    Article  Google Scholar 

  • Jarke, M., Jeusfeld, M., Quix, C., & Vassiliadis, P. (1999). Architecture and quality in data warehouses: An extended repository approach. Information Systems, 24(3), 229–253.

    Article  Google Scholar 

  • Joshi, H., Seker, R., Bayrak, C. S. R., & Connelly, J. (2007). Ontology for disaster mitigation and planning. Paper presented at the summer computer simulation conference, San Diego, CA.

    Google Scholar 

  • Kaneiwa, K., & Mizoguchi, R. (2004, June 2–5). Ontological knowledge base reasoning with sort-hierarchy and rigidity. Paper presented at the ninth international conference on the principles of knowledge representation and reasoning (KR2004), Whistler, BC, Canada.

    Google Scholar 

  • Kemp, E. A. (1996). The role of the individual project in teaching knowledge acquisition. Paper presented at the international conference on software engineering: Education and practice (SE:EP ‘96), Dunedin, New Zealand.

    Google Scholar 

  • Kim, H. M., Fox, M. S., & Sengupta, A. (2007). How to build enterprise data models to achieve compliance to standards or regulatory requirements (and share data). Journal of the Association for Information Systems, 8(2), 105–128.

    Google Scholar 

  • Kwan, M., & Balasubramanian, P. (2003). KnowledgeScope: Managing knowledge in context. Decision Support Systems, 35(4), 467.

    Article  Google Scholar 

  • Mansingh, G., Osei-Bryson, K.-M., & Reichgelt, H. (2009). Building ontology-based knowledge maps to assist knowledge process outsourcing decisions. Knowledge Management Research and Practice, 7, 37–51.

    Article  Google Scholar 

  • Nakhimovsky, Y., Schusteritsch, R., & Rodden, K. (2006). Scaling the card sort method to over 500 items: Restructuring the Google AdWords Help Center. Paper presented at the conference on human factors in computing systems CHI ‘06 Montréal, QC, Canada.

    Google Scholar 

  • Noy, N. (2004). Semantic integration: A survey of ontology based approaches. SIGMOD Record, 33(4), 65–69.

    Article  Google Scholar 

  • Noy, N., & Hafner, C. (1997). The state of the art in ontology design. AI Magazine, 18(3), 53–74.

    Google Scholar 

  • Osei-Bryson, K.-M., Millar, H., Joseph, A., & Mobolurin, A. (2002). Using formal MS/OR modeling to support disaster recovery planning. European Journal of Operational Research, 141(3), 679–688.

    Article  Google Scholar 

  • Peffers, K., & Gengler, C. E. (2003). How to identify new high-payoff information systems for the organization. Communications of the ACM, 46(1), 83–88.

    Article  Google Scholar 

  • Pike, S. D. (2003). The use of repertory grid analysis to elicit salient short break holiday attributes. Journal of Travel Research, 41(3), 326–330.

    Article  Google Scholar 

  • Pinto, H. S., & Martins, J. P. (2004). Ontologies: How can they be built? Knowledge and Information Systems, 6(4), 441–464.

    Article  Google Scholar 

  • Pirolli, P. (2006). Assisting people to become independent learners in the analysis of intelligence: Final technical report (CDRL A002). Arlington, CA: Palo Alto Research Center.

    Google Scholar 

  • Rao, L., & Osei-Bryson, K.-M. (2007). Towards defining dimensions of knowledge systems quality. Expert Systems with Applications, 33(2), 368–378.

    Article  Google Scholar 

  • Reichgelt, H., & Shadbolt, N. (1992). ProtoKEW: A knowledge-based systems for knowledge acquisition. In D. Sleeman & O. Bernsen (Eds.), Research advances in cognitive science: Artificial intelligence (Vol. 5, pp. 171–200). Mahwah, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Ryan, G. W., & Bernard, H. R. (2000). Data management and analysis methods. In N. Denzin & Y. Lincoln (Eds.), Handbook of qualitative research (pp. 769–802). Thousand Oaks, CA: Sage.

    Google Scholar 

  • Shadbolt, N., & Burton, A. M. (1989). The empirical study of knowledge elicitation techniques. ACM SIGART Bulletin, 108, 15–18.

    Article  Google Scholar 

  • Sharma, S., & Osei-Bryson, K.-M. (2008, January 7–10). Organization-ontology based framework for implementing the business understanding phase of data mining projects. Paper presented at the 41st annual hawaii international conference on system sciences, Big Island, Hawaii.

    Google Scholar 

  • Sicilia, M.-A., Lytras, M., Rodriguez, E., & Garcia-Barriocanal, E. (2006). Integrating descriptions of knowledge management learning activities into large ontological structures: A case study. Data & Knowledge Engineering, 57(2), 111–121.

    Article  Google Scholar 

  • Staab, S., Schnurr, H.-P., Studer, R., & Sure, Y. (2001). Knowledge processes and ontologies. IEEE Intelligent Systems, 16(1), 26–34.

    Article  Google Scholar 

  • Sure, Y., Erdmann, M., Angele, J., Staab, S., Studer, R., & Wenke, D. (2002). OntoEdit: Collaborative ontology development for the semantic web. Paper presented at the first international semantic web conference (ISWC 2002), Sardinia, Italy.

    Google Scholar 

  • Upchurch, L., Rugg, G., & Kitchenham, B. (2001). Using card sorts to elicit web page quality attributes. IEEE Software, 18(4), 84–89.

    Article  Google Scholar 

  • Vassiliadis, P., Bouzeghoub, M., & Quix, C. (2000). Towards quality-oriented data warehouse usage and evolution. Informations Systems, 25(2), 89–115.

    Article  Google Scholar 

  • Wagner, W. P., & Zubey, M. L. (2005). Knowledge acquisition for marketing expert systems based upon marketing problem domain characteristics. Marketing Intelligence & Planning, 23(4), 403–416.

    Article  Google Scholar 

  • Walther, C. (1988). Many-sorted unification. Journal of the ACM, 35(1), 1–17.

    Article  Google Scholar 

  • Wand, Y., & Wang, R. Y. (1996). Anchoring data quality dimensions in ontological foundations. Communications of the ACM, 39(11), 86–95.

    Article  Google Scholar 

  • Wang, R. Y., Storey, V. C., & Firth, C. P. (1995). A framework for analysis of data quality research. IEEE Transactions on Knowledge and Data Engineering, 7(4), 623–640.

    Article  Google Scholar 

  • Wang, Y., Sure, Y., Stevens, R., & Rector, A. (2006). Knowledge elicitation plug-in for Protégé: Card sorting and laddering. Paper presented at the Asian semantic web conference (ASWC ‘06), Beijing, China.

    Google Scholar 

  • Wold, G. H. (2002). Disaster recover planning process. Disaster Recovery Journal, 5(1), 29–34.

    Google Scholar 

  • Zhang, H., Kishore, R., Sharman, R., & Ramesh, R. (2007). Agile integration modeling language (AIML): A conceptual modeling grammar for agile integrative business information systems. Decision Support Systems, 44(1), 266–284.

    Article  Google Scholar 

Download references

Acknowledgement

Portions of this chapter have appeared in “An Approach for Ontology Development and Assessment using a Quality Framework,” Knowledge Management Research & Practice (2009) 7, 260–276.

Author information

Authors and Affiliations

  1. Mona School of Business and Management, The University of the West Indies, Mona Campus, Jamaica

    Lila Rao

  2. School of Computing and Software Engineering, Southern Polytechnic State University, Marietta, GA, USA

    Han Reichgelt

  3. Department of Information Systems, Virginia Commonwealth University, Richmond, VA, USA

    Kweku-Muata Osei-Bryson

Authors
  1. Lila Rao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Han Reichgelt
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kweku-Muata Osei-Bryson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lila Rao .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Virginia Commonwealth University, Richmond, Virginia, USA

    Kweku-Muata Osei-Bryson

  2. Department of Computing, University of the West Indies, Mona, Mona Campus, Jamaica

    Gunjan Mansingh

  3. Mona School of Business, University of the West Indies, Mona, Mona Campus, Jamaica

    Lila Rao

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this chapter

Cite this chapter

Rao, L., Reichgelt, H., Osei-Bryson, KM. (2014). A Methodology for Developing High Quality Ontologies for Knowledge Management. In: Osei-Bryson, KM., Mansingh, G., Rao, L. (eds) Knowledge Management for Development. Integrated Series in Information Systems, vol 35. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7392-4_8

Download citation

Publish with us

Policies and ethics

Search

Navigation