Software-engineering challenges of building and deploying reusable problem solvers

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM

Volumn 23, Issue 4, 2009, Pages 339-356

  O'Connor, Martin J ^a   Nyulas, Csongor ^a   Tu, Samson ^a   Buckeridge, David L ^b   Okhmatovskaia, Anna ^a   Musen, Mark A ^a  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b MCGILL UNIVERSITY   (Canada)

Author keywords

Knowledge Based Systems; Problem Solving Methods; Reusable Problem Solvers; Software Engineering Challenges; TaskMethod Decomposition Process

Indexed keywords

ANALYTIC METHOD; AUTHORING TOOL; BUILDING BLOCKES; BUILDING SYSTEMS; CONCEPTUAL MODELING; DECOMPOSITION PROCESS; DOMAIN KNOWLEDGE; DOMAIN ONTOLOGIES; ENGINEERING CHALLENGES; FUNDAMENTAL PRINCIPLES; HIGH-THROUGHPUT; INTELLIGENT APPLICATIONS; NEW OPPORTUNITIES; PROBLEM SOLVERS; PROBLEM SOLVING METHODS; PUBLIC LIBRARY; RE-USABLE ALGORITHMS; SOFTWARE COMPONENT; SOFTWARE SYSTEMS; STRUCTURING KNOWLEDGE;

BUILDINGS; COMPUTER SOFTWARE REUSABILITY; KNOWLEDGE BASED SYSTEMS; KNOWLEDGE ENGINEERING; LIBRARIES; ONTOLOGY; PULSE MODULATION; SOFTWARE ENGINEERING;

PROBLEM SOLVING;

EID: 74049159911     PISSN: 08900604     EISSN: 14691760     Source Type: Journal    
DOI: 10.1017/S0890060409990047     Document Type: Article

References (42)

1. Bellifemine, F.L., Caire, G., & Greenwood, D. (2007). Developing Multi- Agent Systems with JADE. Hoboken, NJ: Wiley.
2. Benjamins, R. (2008). Near term prospects for semantic technologies. IEEE Intelligent Systems 23(1), 76-88.
3. Benjamins, R., Decker, S., Fensel, D., Motta, E., Schreiber, G., Studer, R., & Wielinga, B. (1998). IBROW3-An intelligent brokering service for knowledge-component reuse on the World Wide Web. Proc. 11th Banff Knowledge Acquisition for Knowledge-Based Systems Workshop.
4. Buckeridge, D.L., Okhmatovskaia O., Tu, S.W., O'Connor,M.J., Nyulas, C.I., & Musen, M.A. (2008). Understanding detection performance in public health surveillance: modeling aberrancy-detection algorithms. Journal of the American Medical Informatics Association 15(6), 760-769.
5. Buckeridge, D.L., Burkom, H., Moore, A.W., Pavlin, J.A., Cutchis, P.N., & Hogan,W. (2004). Evaluation of syndromic surveillance systems: development of an epidemic simulation model. Syndromic Surveillance: Reports from a National Conference. Morbidity and Mortality Weekly Report 53(Suppl.), 137-143.
6. Buckeridge, D.L., Graham, J., O'Connor, M.J., Choy, M.K., Tu, S.W., & Musen, M.A. (2002). Knowledge-based bioterrorism surveillance. AMIA Annual Symp., pp. 76-80. Bethesda, MD: American Medical Informatics Association.
7. Buckeridge, D.L., O'Connor, M.J., Xu, H.,&Musen, M.A. (2004).A knowledge- based framework for deploying surveillance problem solvers. Int. Conf. Information and Knowledge Engineering (IKE '04), Las Vegas, NV.
8. Buehler, J.W., Berkelman, R.L., Hartley, D.M., & Peters, C.J. (2003). Syndromic surveillance and bioterrorism-related epidemics. Emerging Infectious Diseases 9(10), 1197-1204.
9. Carriero, N., & Gelertner, D. (1989). How to write parallel programs: a guide to the perplexed. ACM Computing Surveys 21(3), 323-357.
10. Chandrasekaran, B. (1986). Generic tasks in knowledge-based reasoning: high-level building blocks for expert systems design. IEEE Expert 1(3), 23-30.
11. Chandrasekaran, B. (2009). Problem solving methods and knowledge systems: a personal journey to perceptual images as knowledge. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 23(4), 331-338 [this issue].
12. Chandrasekaran, B., Johnson, T.,&Smith, J.W. (1992). Task structure analysis for knowledge modeling. Communications of the ACM 33(9), 124-136.
13. Clancey, W.J. (1986). From GUIDON to NEOMYCIN to HERACLES in twenty short lessons. AI Magazine 7(3), 40-60.
14. Clancey, W.J., Sierhius, M., & Seah, C. (2009).Workflow agents versus expert systems: problem solving methods in work systems design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 23(4), 357-371 [this issue].
15. Crubézy, M., Motta, E., Lu,W., & Musen, M.A. (2003). Configuring online problem-solving resources with the internet reasoning service. IEEE Intelligent Systems 18(2), 34-42.
16. Crubézy, M., O'Connor, M.J., Buckeridge, D.L., Pincus, Z., & Musen, M.A. (2005). Ontology-centered syndromic surveillance for bioterrorism. IEEE Intelligent Systems 20(5), 26-35.
17. Crubézy, M., & Musen, M.A. (2004). Ontologies in support of problem solving. In Handbook on Ontologies (Staab, S., & Studer, R., Eds.), pp. 321-342. Berlin: Springer.
18. Domingue, J., & Fensel, D. (2009). Problem solving methods in a global networked age. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 23(4), 373-390 [this issue].
19. Eriksson, H., Puerta, A.R., Gennari, J.H., Rothenfluh, T.E., Tu, S.W., & Musen, M.A. (1995). Custom-tailored development tools for knowledgebased systems. Proc. 9th Banff Knowledge Acquisition for Knowledge- Based Systems Workshop.
20. Fensel, D., & Groenboom, R. (1997). Specifying knowledge-based systems with reusable components. Proc. 9th Int. Conf. Software Engineering, pp. 18-20.
21. Fensel, D., Motta, E., Benjamins, V.R., Crubézy, M., Decker, S., Gaspari, M., Groenboom, R., Grosso,W., van Harmelen, F., Musen, M.A., Plaza, E., Schreiber, G., Studer, R., & Wielinga, B. (2002). The unified problem- solving method development language UPML. Knowledge and Information Systems 5(1), 83-131.
22. Gennari, J.H., Fergerson, R.W., Grosso, W.E., Crubézy, M., Eriksson, H., Noy, N., & Tu, S.W. (2003). The evolution of Protégé: an environment for knowledge-based system development. International Journal of Human- Computer Studies 1(58), 89-123.
23. Gennari, J.H., Tu, S.W., Rothenfluh, T.E., & Musen, M.A. (1994). Mapping domains to methods in support of reuse. International Journal of Human- Computer Studies 41, 399-424.
24. Halter, S. (2002). JavaSpaces Example by Example. NewYork: PrenticeHall.
25. IBM. (2006). Model-driven software development. IBM Systems Journal 45(3), 449.
26. Knublauch, H., Fergerson, R., Noy, N.F., & Musen, M.A. (2004). The Prote ́gé OWL plugin: an open development environment for Semantic Web applications. Third Int. Semantic Web Conf., pp. 229-243, Hiroshima.
27. Lombardo, J., Burkom, H., Elbert, E., Magruder, S., Lewis, S.H., Loschen, W., Sari, J., Sniegoski, C., Wojcik, R., & Pavlin, J. (2003). A systems overview of the electronic surveillance system for the early notification of community-based epidemics (ESSENCE II). Journal of Urban Health 80(2, Suppl. 1), i32-i42.
28. Marcus, S., Stout J.,&McDermott, J. (1988). VT: an expert elevator designer that uses knowledge-based backtracking. AI Magazine 9(1), 95-111.
29. Martin, D., Burstein, M., Hobbs, J., Lassila, O., McDermott, D., McIlraith, S., Narayanan, S., Paolucci, M., Parsia, B., Payne, T., Sirin, E., Srinivasan, N., & Sycara, K. (2004). OWL-S: semantic markup for Web services. Proc. W3C. Accessed at http://www.w3.org/Submission/2004/ SUBM-OWL-S-20041122/
30. McDermott, J.P., & Bachant, J. (1984). R1 revisited: four years in the trenches. AI Magazine 5(3), 21-32.
31. McDonald, C.J., Huff, S.M., Suico., J.G., Hill, G. Leavelle, D., Aller, R., Forrey, A., Mercer, K., DeMoor, G., Hook, J.,Williams,W., Case, J., & Maloney, P. (2003). LOINC, a universal standard for identifying laboratory observations: a 5-year update. Clinical Chemistry 49, 624-633.
32. Musen, M.A., & Schreiber, G. (1995). Architectures for intelligent systems based on reusable components. Artificial Intelligence in Medicine 7(3), 189-199.
33. Nyulas, C.I., O'Connor, M.J., Tu, S.W., Okhmatovskaia, A., Buckeridge, D., & Musen, M.A. (2008). An ontology-driven framework for deploying JADE agent systems. IEEE/WIC/ACM International Conf. Intelligent Agent Technology, pp. 573-577, Sydney, Australia.
34. OWL. (2004). Accessed at www.w3.org/TR/owl-ref
35. Pincus, Z., & Musen. M.A. (2003). Contextualizing heterogeneous data for integration and inference. AMIA Annual Symp., pp. 514-518. Bethesda, MD: American Medical Informatics Association.
36. R. (2009). Accessed at http://www.r-project.org in January 2009.
37. Rothenfluh, T.E., Gennari, J., Eriksson, H., Puerta, A.R., Tu, S.W.,&Musen, M.A. (1995). Reusable ontologies, knowledge-acquisition tools, and performance systems: PROTEGE-II solutions to Sisyphus-2. International Journal of Human-Computer Studies 44(3-4), 303-332.
38. Schreiber, G., Akkermans, H., Anjewierden, A., de Hoog, R., Shadbolt, N., Van de Velde, W., & Wielinga, B. (1999). Knowledge Engineering and Management: The CommonKADS Methodology. Cambridge, MA: MIT Press.
39. Steels, L. (1990). Components of expertise. AI Magazine 11(2), 30-49.
40. Steinberg, D., Budinsky, F., Paternostro, M., & Merks, E. (2008). EMF: Eclipse Modeling Framework, 2nd ed. Reading, MA: Addison-Wesley.
41. Tu, S.W., Eriksson, H., Gennari, J.H. Shahar, Y., & Musen, M.A. (1995). Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools: application of PROTÉ GÉ -II to protocol-based decision support. Artificial Intelligence in Medicine 7(3), 257-289.
42. Tsui, F.C., Espino, J.U., Dato, V.M., Gesteland, P.H., Hutman, J.,&Wagner, M.M. (2003). Technical description of RODS: a real-time public health surveillance system. Journal of the American Medical Informatics Association 10(5), 399-408.