An experimental study of the effects of representing property precedence on the comprehension of conceptual schemas

Journal of the Association for Information Systems

Volumn 12, Issue 6, 2011, Pages 441-462

  Parsons, Jeffrey ^a  

^a MEMORIAL UNIVERSITY OF NEWFOUNDLAND   (Canada)

Author keywords

Comprehension; Conceptual modeling; Experimental design; Ontology; Property precedence

Indexed keywords

DESIGN OF EXPERIMENTS; ONTOLOGY; REQUIREMENTS ENGINEERING; SEMANTICS;

COMPREHENSION; CONCEPTUAL MODEL; CONCEPTUAL SCHEMA DIAGRAMS; INFORMATION SYSTEMS REQUIREMENTS; LABORATORY EXPERIMENTS; MODELING CONSTRUCT; PROPERTY PRECEDENCE; THEORETICAL FOUNDATIONS;

DATA MINING;

EID: 79960809679     PISSN: 15583457     EISSN: 15369323     Source Type: Journal    
DOI: 10.17705/1jais.00268     Document Type: Article

References (38)

1. Allen, G., & March, S. (2006). The effects of state-based and event-based data representations on user performance in query formulation tasks. MIS Quarterly, 30(2), 269-290.
2. Allen, G., & Parsons, J. (2010). Is query reuse potentially harmful? Anchoring and adjustment in adapting existing database queries. Information Systems Research, 21(1), 56-77.
3. Bodart, F., Patel, A., Sim, M., & Weber, R. (2001). Should the optional property construct be used in conceptual modeling? A theory and three empirical tests. Information Systems Research, 12(4), 384-405.
4. Boehm, B. W. (1981). Software engineering economics: Advances in computing science and technology. Englewood Cliffs, NJ: Prentice-Hall.
5. Bowen, P., O'Farrell, R., & Rohde, F. (2006). Analysis of competing data structures: Does ontological clarity produce better end user query performance. Journal of the Association for Information Systems, 7(8), 514-544.
6. Bunge, M. (1977). Treatise on basic philosophy (Volume 3), Ontology I: The furniture of the world. Boston: Reidel.
7. Bunge, M. (1979). Treatise on basic philosophy (Volume 4), Ontology II: A world of systems. Boston: Reidel.
8. Burton-Jones, A. & Meso, P. (2008). The effects of decomposition quality and multiple forms of information on novices' understanding of a domain from a conceptual model. Journal of the Association for Information Systems, 9(12), 748-802.
9. Burton-Jones, A., Wand, Y., & Weber, R. (2009). Guidelines for empirical evaluations of conceptual modeling grammars. Journal of the Association for Information Systems, 10(6), 495-532.
10. Burton-Jones, A. & Weber, R. (1999). Understanding relationships with attributes in entity relationship diagrams. In P. De & J. DeGross (Eds.), Proceedings of the Twentieth International Conference on Information Systems, Charlotte, NC, 214-228.
11. Burton-Jones, A. & Weber, R. (2003). Properties do not have properties: Investigating a questionable conceptual modeling practice. In D. Batra, J. Parsons & V. Ramesh (Eds.), Proceedings of the Second Annual Symposium on Research in Systems Analysis and Design, Miami, 14 pp.
12. Byrd, T., Cossick, K., & Zmud, R. (1992). A synthesis of research on requirements analysis and knowledge acquisition techniques. MIS Quarterly, 16(1), 117-138.
13. Chen, P. (1976). The entity-relationship model: Toward a unified view of data. ACM Transactions on Database Systems, 1(1), 9-36.
14. Davies, I., Green, P., Rosemann, M., Indulska, M., & Gallo, S. (2006). How do practitioners use conceptual modeling in practice? Data and Knowledge Engineering, 58(3), 358-380.
15. Dobing, B., & Parsons, J. (2000). Understanding the role of use cases in UML: A review and research agenda. Journal of Database Management, 11(4), 28-36.
16. Dobing, B., & Parsons, J. (2006). How UML is used. Communications of the ACM, 49(5), 109-113.
17. Dobing, B., & Parsons, J. (2008). Dimensions of UML diagram use: A survey of practitioners. Journal of Database Management, 19(1), 1-18.
18. Evermann, J. (2005). The association construct in conceptual modelling - An analysis using the Bunge ontological model. In O. Pastor & J. Falcao e Cunha (Eds.). Proceedings of the 2005 Conference on Advanced Information Systems Engineering (CAiSE'05), LNCS 3520, 33-47.
19. Evermann, J., & Wand, Y. (2005). Ontology based object-oriented domain modelling: Fundamental concepts. Requirements Engineering Journal, 10(2), 146-160.
20. Evermann, J., & Wand, Y. (2006). Ontological modeling rules for UML: An empirical assessment. Journal of Computer Information Systems, 46(5), 14-29.
21. Fettke, P. (2009). How conceptual modeling is used. Communications of the Association for Information Systems, 25(1), 571-592.
22. Gemino, A., & Wand, Y. (2003). Evaluating modeling techniques based on models of learning. Communications of the ACM, 46(10), 79-84.
23. Gemino, A., & Wand, Y. (2004). A framework for empirical evaluation of conceptual modeling techniques. Requirements Engineering Journal, 9(4), 248-260.
24. Gemino, A., & Wand, Y. (2005). Complexity and clarity in conceptual modeling: Comparison of mandatory and optional properties. Data and Knowledge Engineering, 55(3), 301-326.
25. Gemino, A., & Wand, Y. (2003). Foundations for empirical comparisons of conceptual modeling techniques. In D. Batra, J. Parsons & V. Ramesh (Eds.), Proceedings of the Second Annual Symposium on Research in Systems Analysis and Design, Miami, FL, 29 pp.
26. Hoffer, J., Prescott, M., & McFadden, F. (2008). Modern database management (Eighth Edition), Upper Saddle River, NJ: Prentice Hall.
27. Khatri, V., Vessey, I., Ramesh, V., Clay, P., & Park, S. (2006). Understanding conceptual schemas: Exploring the role of application and IS domain knowledge. Information Systems Research, 17(1), 81-99.
28. Mayer, R. (2001). Multimedia learning. Cambridge, MA: Cambridge University Press.
29. Parsons, J., & Cole, L. (2005). What do the pictures mean? Guidelines for experimental evaluation of representation fidelity in diagrammatical conceptual modeling techniques. Data and Knowledge Engineering, 55(3), 327-342.
30. Parsons, J., & Wand, Y. (2003). Attribute-based semantic reconciliation of multiple data sources. Journal on Data Semantics 1, LNCS 2800, 21-47.
31. Rob, P., & Coronel, C. (2009). Database systems: Design, implementation, and management. Boston, MA: Course Technology.
32. Siau, K., Wand, Y., & Benbasat, I. (1997). The relative importance of structural constraints and surface semantics in information modeling. Information Systems, 22(2-3), 155-170.
33. ter Hofstede, A. & van der Weide, Th P. (1993). Expressiveness in conceptual data modelling. Data and Knowledge Engineering, 10(1), 65-100.
34. Wand, Y., Storey, V., & Weber, R. (1999). An ontological analysis of the relationship construct in conceptual modeling. ACM Transactions on Database Systems, 24(4), 494-528.
35. Wand, Y. & Weber, R. (1990). An ontological model of an information system. IEEE Transactions on Software Engineering, 16(11), 1282-1292.
36. Wand, Y., & Weber, R. (1993). On the ontological expressiveness of information systems analysis and design grammars. Journal of Information Systems, 3(4), 217-237.
37. Wand, Y. & Weber, R. (2002). Information systems and conceptual modeling: A research agenda. Information Systems Research, 13(4), 363-376.
38. Weber, R. (1997). Ontological foundations of information systems. Melbourne: Coopers & Lybrand