A measurement ontology generalizable for emerging domain applications on the Semantic Web

Journal of Database Management

Volumn 18, Issue 1, 2007, Pages 20-42

  Kim, Henry M ^a   Sengupta, Arijit ^b   Fox, Mark S ^c   Dalkilic, Mehmet ^d  

^a YORK UNIVERSITY   (Canada)

^b WRIGHT STATE UNIVERSITY   (United States)

^c UNIVERSITY OF TORONTO   (Canada)

^d INDIANA UNIVERSITY   (United States)

Author keywords

Measurement; Microarray analysis; Ontological engineering; Ontology; Quality control; Quality of service (QoS); Semantic Web

Indexed keywords

CONSTRAINT THEORY; DATA PROCESSING; ONTOLOGY; QUALITY CONTROL; QUALITY OF SERVICE; SOFTWARE AGENTS;

DOMAIN-SPECIFIC ONTOLOGIES; MEASUREMENT CONCEPTS; MICROARRAY ANALYSIS; ONTOLOGICAL ENGINEERING;

SEMANTIC WEB;

EID: 34147137735     PISSN: 10638016     EISSN: 15338010     Source Type: Journal    
DOI: 10.4018/jdm.2007010102     Document Type: Article

References (60)

1. Allen, J. F. (1983). Maintaining knowledge about temporal intervals. Communications of the ACM, 25(11), 832-843.
2. Ashburner, M., Ball, C., Blake, J., Botstein, D., Butler, H., Cherry, J., et al. (2000). Gene ontology: Tool for the unification of biology. National Genetics, 25, 25-29.
3. Attie, A. D. (2003). The new industrialized approach to biology. Cell Biology Education, 2, 150-151.
4. Bechhofer, S., Goble, C., & Horrocks, I. (2001, July 30-August 1). DAML+OIL Is not Enough. Paper presented at the First Semantic Web Working Symposium (SWWS-01), Stanford, CA.
5. Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American, 284(5), 34-43.
6. Bowers, S., & Ludäscher, B. (2004). An ontology-driven framework for data transformation in scientific work-flows. Paper presented at the International Workshop on Data Integration in the Life Sciences (OILS'04), Leipzig, Germany.
7. Brilhante, V., & Robertson, D. (2001). Metadata-Supported Automated Ecological Modelling. In C. Rautenstrauch (Ed.), Environmental information systems in industry and public administration. Hershey, PA: Idea Group Publishing.
8. Campbell, A. E., & Shapiro, S. C. (1995). Ontological mediation: An overview. Paper presented at the IJCAI Workshop on Basic Ontological Issues in Knowledge Sharing.
9. Chen, Y., Zhou, L., & Zhang, D. (2006). Ontology-supported Web service composition: An approach to service-oriented knowledge management in corporate services. Journal of Database Management, 17(1), 67-84.
10. Davies, J., Duke, A., & Stonkus, A. (2002). OntoShare: Using ontologies for knowledge sharing. Paper presented at the Semantic Web Workshop of the WWW Conference, Hawaii, HI.
11. Duggan, D. J., Chen, M., Meltzer, P., & Trent, J. (1999). Expression profiling using cDNA microarrays. Nature Genetics, 21, 10-14.
12. Fenton, N. E. (1994). Software measurement: a necessary scientific basis. IEEE Transactions on Software Engineering, 20(3), 199-206.
13. Fikes, R., & Farquhar, A. (1999). Distributed repositories of highly expressive reusable ontologies. IEEE Intelligent Systems, 14(2), 73-79.
14. Finkelstein, L. (1984). A review of the fundamental concepts of measurement. Measurement, 2(1), 25-34.
15. Fox, M. S. (1992). The TOVE project, towards a common sense model of the enterprise. In C. Petrie (Ed.), Enterprise integration. Cambridge, MA: MIT Press.
16. Fox, M. S., & Gruninger, M. (1998). Enterprise modelling. AI Magazine, 19(3), 109-121.
17. Gandon, F. (2001, October 22-24). Engineering an ontology for a multi-agents corporate memory system. Paper presented at the ISMICK 2001 Eighth International Symposium on the Management of Industrial and Corporate Knowledge, Université de Technologie de Compiègne, France.
18. Gandon, F. L., & Sadeh, N. M. (2004). Semantic Web technologies to reconcile privacy and context awareness. Journal of Web Semantics, 1(3), 241-260.
19. Goh, C. H., Bressan, S., Madnick, S., & Siegel, M. (1999). Context interchange: New features and formalisms for the intelligent integration of information. ACM Transactions on Information Systems, 17(3), 270-293.
20. Grady, J. O. (1993). System requirements analysis: McGraw-Hill Inc.
21. Gruber, T. R. (1993, March). Towards principles for the design of pntologies used for knowledge sharing. Paper presented at the International Workshop on Formal Ontology, Padova, Italy.
22. Gruber, T. R., & Olsen, G. R. (1994). An ontology for engineering mathematics. Paper presented at the Fourth International Conference on Principles of Knowledge Representation and Reasoning, Bonn, Germany.
23. Gruninger, M., & Fox, M. S. (1995). Methodology for the design and evaluation of ontologies. Paper presented at the Workshop on Basic Ontological Issues in Knowledge Sharing, IJCAI-95, Montreal, Canada.
24. Hayes, P. J. (1985). Naive physics I: Ontology for liquids. In J. Hobbs & B. Moore (Eds.), Theories of the commonsense world (pp. 71-89). Ablex Publishing Corp.
25. Heflin, J. (2000, April 3, 2000). Measurement ontology 1.0 (draft). Retrieved August 15, 2004, from http://www.cs.umd.edu/projects/plus/SHOE/onts/ measure1.0.html
26. Hewett, M., Oliver, D. E., Rubin, D. L., Easton, K. L., Stuart, J. M., Altman, R. B., et al. (2002). PharmGKB: the pharmaco-genetics knowledge base. Nucleic Acids Research, 30(1), 163-165.
27. Khatri, V., Ram, S., & Snodgrass, R. T. (2004). Augmenting a conceptual model with geospatiotemporal annotations. IEEE Transactions on Knowledge and Data Engineering, 75(11), 1324-1338.
28. Kim, H. M. (1999). Representing and reasoning about quality using enterprise models. Unpublished PhD thesis, Department of Industrial Engineering, University of Toronto, Toronto, Ontario, Canada.
29. th Annual Hawaii International Conference on Systems Science (HICSS-35), Hawaii, HI.
30. th Hawaii International Conference on Systems Science (HICSS), Big Island, HI.
31. Kim, H. M., Fox, M. S., & Grüninger, M. (1999). An ontology for quality management: Enabling quality problem identification and tracing. BT Technology Journal, 77(4), 131-139.
32. th Annual Hawaii International Conference on System Sciences (HICSS'04), Big Island, HI.
33. Kuipers, B. J. (1986). Qualitative simulation. Artificial Intelligence, 29(3), 289-338.
34. Lenat, D. B. (1995). CYC: A large-scale investment in knowledge infrastructure. Communications of the ACM, 35(11), 33-38.
35. Lesk, A. M. (2005). Databasse annotation in molecular biology, principles and practice: John Wiley & Sons Ltd.
36. Lozano-Tello, A., & Gomez-Perez, A. (2004). ONTOMETRIC: A method to choose the appropriate ontology. Journal of Database Management, 15(2), 1-18.
37. Mars, N. J. I. (1993, March 10-13). An ontology of measurement units. Paper presented at the International Workshop on Formal Ontologies in Conceptual Analysis and Knowledge Representation, Padova, Italy.
38. Massey, B. S. (1971). Units, dimensional analysis, and physical similarity. London: Van Nostrom Reinhold.
39. McCarthy, J., & Hayes, P. J. (1969). Some philosophical problems from the standpoint of AI. In B. Meltzer & D. Michie (Eds.), Machine intelligence (Vol. 4, pp. 463-501). Edinburgh, UK: Edinburgh University Press.
40. McGuinness, D. L., & van Harmelen, F. (2003). OWL Web Ontology Language overview (No. CR-owl-features-20030818). W3C.
41. Milton, S. K., & Kazmierczak, E. (2004). An ontology of data modelling languages: A study using a common-sense realistic ontology. Journal of Database Management, 15(2), 19-38.
42. Mount, D. W. (2004). Bioinformatics sequence and genome analysis. Cold Spring Harbor, New York: Cold Spring Harbor Laboratory Press.
43. Narens, L. (1985). Abstract measurement theory. Cambridge, MA: MIT Press.
44. Novak, G. S., Jr. (1995). Conversion of units of measurement. IEEE Transactions on Software Engineering, 21(8), 651-661.
45. Noy, N. F., & Hafner, C. D. (1997). The state of the art in ontology sesign: A survey and comparative review. AI Magazine, 18(3), 53-74.
46. th Annual Hawaii International Conference on System Sciences, Big Island, HI.
47. Pease, A., & Niles, I. (2002). IEEE standard upper ontology: A progress report. Knowledge Engineering Review, 17, 65-70.
48. Ram, S., & Wei, W. (2004). Modeling the semantics of 3D protein structures. Paper presented at the ER 2004, Shanghai, China.
49. Reiger, C., & Grinberg, M. (1977). The declarative representation and procedural simulations of causality in physical mechanisms. Paper presented at the Joint Conference on Artificial Intelligence.
50. Retz-Schmidt, G. (1988). Various views on spatial prepositions. AI Magazine, 9(2), 95-105.
51. Roberts, F. (1979). Measurement theory with applications to decision making, utility and the social sciences. Reading, MA: Addison-Wesley.
52. Ronco, L., Grossel, M., Zimmer, M., & Socash, T. (2003). Modules in emerging fields. Vol 4: Genomics and proteomics.
53. SAP-AG. (1995). SAP R/3 system: Quality management (No. 4.6). Neurottstrasse 16, 69190 Walldorf, Germany: SAP AG.
54. Scheaffer, R. L., & McClave, J. T. (1982). Statistics for engineers. Boston, MA: PWS Publishers.
55. Schienoff, C., Balakirsky, S., Uschold, M., Provine, R., & Smith, S. (2003). Using ontologies to aid navigation planning in autonomous vehicles. The knowledge engineering review, 18, 243-255.
56. Stevens, R., Goble, C., Horrocks, I., & Bechhofer, S. (2002). Building a bioinformatics ontology using OIL. IEEE Transactions on Information Technology in Biomedicine, 6(2), 135-141.
57. Stevens, R., Goble, C. A., & Bechhofer, S. (2000). Ontology-based knowledge representation for bioinformatics. Briefings in Bioinformatics, 1(4), 398-414.
58. Stoeckert Jr., C. J., & Parkinson, H. (2004). The MGED ontology: A framework for describing functional genomics experiments. Comparative and Functional Genomics, 4(1), 127-132.
59. Uschold, M., & Gruninger, M. (1996). Ontologies: Principles, methods and applications. Knowledge Engineering Review, 11(2), 93-136.
60. Wroe, C., Stevens, R., Goble, C., & Ashburner, M. (2003). A methodology to migrate the gene ontology to a description logic environment using DAML+OIL. Pacific Symposium on Biocomputing, 8, 624-635.