SATISFYING USER EXPECTATIONS IN ONTOLOGY-DRIVEN COMPOSITIONAL SYSTEMS - A Case Study in Fish Population Modeling

Mitchell G. Gillespie, Deborah A. Stacey, Stephen S. Crawford

Abstract

Ontology-Driven Compositional Systems (ODCSs) are designed to assist a user with semi- or fully automatic composition of a desired system. Current research with ODCSs has been conducted around the discovery and composition of web services and alternatively a bottom-up resource management approach to automatic system composition. This paper argues that current ODCSs do not truly satisfy user expectations as the semantic knowledge required to make proper discovery, decision-making and composition has not been fully represented. The authors introduce the beginning of their work of utilizing the inheritance of multiple ontologies to fully represent the functional, data, quality & trust, and execution of compositional units within an ODCS. Furthermore, a case study of fish population modeling is presented.

References

  1. Arpinar, I. B., Zhang, R., Alemen-Meza, B., and Maduko, A. (2005). Ontology-driven web services composition platform. Information Systems and e-Buisness Management, 3:175-199.
  2. Cardoso, J. and Sheth, A. (2005). Introduction to semantic web services and web process composition. In First International Workshop on Semantic Web Services and Web Process Composition, Lecture Notes in Computer Science, pages 1-13. Spinger.
  3. Crawford, S., Gillis, D., and Rooney, N. (2008). A review of population level ecological risk assessments for the candu owners group. Technical report, CANDU Owners Group, Toronto, ON, Canada.
  4. Crawford, S., Muir, A., and McCann, K. (2001). Ecological basis for recommendation of 2001 saugeen ojibway commercial harvest tacs for lake whitefish (coregonus clupeaformis) in lake huron, report prepared for the chippewas of nawash first nation. Technical report, University of Guelph, Wiarton, ON, Canada. (revised with references 11 July 2002; revised with response to OMNR comments 02 January 2003).
  5. Duez, P. P., Zuliani, M. J., and Jameison, G. A. (2006). Trust by design: Information requirements for appropriate trust in automation. Technical report, IBM Canada Ltd.
  6. Feller, J. and Fitzgerald, B. (2002). Understanding Open Source Software Development. Addison-Wesley, London.
  7. Gangemi, A., Catenacci, C., Ciaramita, M., and Lehmann, J. (2005). A theoretical framework for ontology evaluation and validation.
  8. Gillis, D., Tey, J., Gillespie, M., and Crawford, S. (2009). Do fisheries biologists have appropriate tools for assessing dynamics of harvested fish populations? Not yet submitted to Journal.
  9. Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5:199- 220.
  10. Hilborn, R. and Walters, C. J. (1992). Quantitative fisheries stock assessment: choice, dynamics and uncertainty. Chapman and Hall, New York.
  11. Hlomani, H. (2009). A bottom-up approach to system composition using ontologies. Master's thesis, University of Guelph, Guelph, ON, Canada.
  12. Hlomani, H. and Stacey, D. (2009). An ontology driven approach to software systems composition. In Proceedings of the 2009 International Conference of Knowledge Engineering and Ontology Development. INSTICC.
  13. Majithia, S., Ali, A. S., Rana, O. F., and Walker, D. W. (2004). Reputation-based semantic service discovery. Enabling Technologies, IEEE International Workshops on, 0:297-302.
  14. Megrey, B. A. and Moksness, E. (2009). Past, present, and future trends in the use of computers in fisheries research, pages 1-30. Computers in Fisheries Research, 2nd Edition. Springer Science.
  15. Meng, X., Junliang, C., Yong, P., Xiang, M., and Chuanchang, L. (2006). A dynamic semantic associationbased web service composition. In Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence. IEEE.
  16. Methot, R. D. J. (2009). Stock assessment: operational models in support of fisheries management, pages 137-165. Fish & Fisheries Series 31. Springer Science, Netherlands.
  17. NRC (2005). Improving fish stock assessments.
  18. Quinn, T. J. and Deriso, R. (1999). Quantitative fish dynamics. Ofxord University Press, New York.
  19. Srivastava, B. and Koehler, J. (2003). Web service composition - current solutions and open problems. In ICAPS 2003 Workshop on Planning for Web Services, Trento, Italy.
  20. Stringer, K., Clemens, M., and Rivard, D. (2009). The changing nature of fisheries management and implications for science, pages 97-111. Fish & Fisheries Series 31. Springer Science, Netherlands.
  21. Tran, V. X. (2008). Wsqosonto: A qos ontology for web services. In 2008 IEEE International Symposium on Service Oriented System Engineering, pages 233-238. IEEE.
  22. Uschold, M. and King, M. (1995). Towards a methodology for building ontologies. In In Workshop on Basic Ontological Issues in Knowledge Sharing, held in conjunction with IJCAI-95.
  23. Walters, C. J. and Martell, S. J. D. (2004). Fisheries Ecology and Management. Princeton University Press, New Jersey.
  24. Wang, X., Vitvar, T., Kerrigan, M., and Toma, I. (2006). A QoS-Aware Selection Model for Semantic Web Services, pages 390-401. Lecture Notes in Computer Science. Springer, Berlin, Germany.
  25. Wang, Y. and Vassileva, J. (2007). Toward trust and reputation based web service selection: A survey. In Proc. Intl. Transactions on Systems Science and Applications, volume 3, pages 118-132.
  26. Zeng, L., Benatallah, B., Dumas, M., Kalagnanam, J., and Sheng, Q. Z. (2003). Quality driven web services composition. In Proceedings of the 12th International conference on the World Wide Web, pages 411-421. ACM.
  27. Zhang, P. and von Dran, G. M. (2002). User expectations and rankings of quality factors in different web site domains. International Journal of Electronic Commerce, 6(2):9-33.
Download


Paper Citation


in Harvard Style

G. Gillespie M., A. Stacey D. and S. Crawford S. (2010). SATISFYING USER EXPECTATIONS IN ONTOLOGY-DRIVEN COMPOSITIONAL SYSTEMS - A Case Study in Fish Population Modeling . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2010) ISBN 978-989-8425-29-4, pages 133-143. DOI: 10.5220/0003103801330143


in Bibtex Style

@conference{keod10,
author={Mitchell G. Gillespie and Deborah A. Stacey and Stephen S. Crawford},
title={SATISFYING USER EXPECTATIONS IN ONTOLOGY-DRIVEN COMPOSITIONAL SYSTEMS - A Case Study in Fish Population Modeling},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2010)},
year={2010},
pages={133-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003103801330143},
isbn={978-989-8425-29-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2010)
TI - SATISFYING USER EXPECTATIONS IN ONTOLOGY-DRIVEN COMPOSITIONAL SYSTEMS - A Case Study in Fish Population Modeling
SN - 978-989-8425-29-4
AU - G. Gillespie M.
AU - A. Stacey D.
AU - S. Crawford S.
PY - 2010
SP - 133
EP - 143
DO - 10.5220/0003103801330143