Abstract
Conceptual modeling is the foundation of system analysis and design methodologies. It is challenging because it requires a clear understanding of an application domain and the ability to translate the requirement specification into a conceptual data model. Semi-automated conceptual data modeling is a process of using an intelligent tool to aid the modeler for the purpose of building a quality conceptual data model. In this paper, we first present six categories of methodologies that can be used for developing conceptual data models. We then describe the characteristics of each category, compare these characteristics, and present related work of each category. We finally suggest a framework for semi-automatically generating conceptual data models from requirements and suggest challenging research topics.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Aguilera, D., García-Ranea, R., Gómez, C., Olivé, A.: An eclipse plugin for validating names in UML conceptual schemas. In: De Troyer, O., Medeiros, C.B., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds.) ER 2011. LNCS, vol. 6999, pp. 323–327. Springer, Heidelberg (2011)
Aguilera, D., Gómez, C., Olivé, A.: A method for the definition and treatment of conceptual schema quality issues. In: Atzeni, P., Cheung, D., Ram, S. (eds.) ER 2012. LNCS, vol. 7532, pp. 501–514. Springer, Heidelberg (2012)
Ambriola, V., Gervasi, V.: On the systematic analysis of natural language requirements with circe. Autom. Softw. Eng. 13, 107–167 (2006)
Alexander, C.: The Timeless Way of Building. Oxford University Press, New York (1979)
Anthony, S., Mellarkod, V.: Data modeling patterns: a method and evaluation. In: Proceedings of the Fifteenth Americas Conference on Information Systems, San Francisco, California (2009)
Atkinson, C., Kuhne, T.: Model-driven development: a metamodeling foundation. IEEE Softw. 20(5), 36–41 (2003)
Batra, D.: Cognitive complexity in data modeling: causes and recommendations. Requirements Eng. 12(4), 231–244 (2007)
Blaha, M.: Patterns of Data Modeling. CRC Press, Boca Raton (2010)
Buchholz, E., Cyriaks, H., Dsterhft, A., Mehlan, H., Thalheim, B.: Applying a natural language dialogue tool for designing databases. In: Proceedings of the first International Workshop on Applications of Natural Language to Databases (NLDB 1995) (1995)
Burton-Jones, A., Meso, P.: How good are these UML diagrams? An empirical test of the Wand and Weber good decomposition model. In: ICIS 2002 Proceedings, 10 (2002)
Chaiyasut, P., Shanks, G.: Conceptual data modeling process: a study of novice and expert data modelers. In: Proceedings of the 1st International Conference on Object-Role Modeling, Australia, University of Queensland (1994)
Chen, P.: English sentence structure and entity-relationship diagram. Inf. Sci. 1(1), 127–149 (1983)
Chen, P.: The entity-relationship model: toward a unified view of data. ACM Trans. Database Syst. 1(1), 9–36 (1976)
Choobineh, J., Lo, A.: CABSYDD: case-based system for database design. J. Manag. Inf. Syst. 21(3), 242–253 (2004)
Coad, P., North, D., Mayfield, M.: Object Models – Strategies, Pattern, and Applications. Yourdon Press, Englewood Cliffs (1995)
Conesa, J., Storey, V.C., Sugumaran, V.: Experiences using the ResearchCyc upper level ontology. In: Kedad, Z., Lammari, N., Métais, E., Meziane, F., Rezgui, Y. (eds.) NLDB 2007. LNCS, vol. 4592, pp. 143–155. Springer, Heidelberg (2007)
Corcho, O., Fernandez-Lopez, M., Gomez-Perez, A.: Methodologies, tools and languages for building ontologies: where is their meeting point? Data Knowl. Eng. 46, 41–64 (2003)
Deeptimahanti, D.K, Sanyal, R.: Semi-automatic generation of UML models from natural language requirements. In: Proceedings of the 4th India Software Engineering Conference (ISEC 2011), pp. 165–174 (2011)
Dehne, F., Steuten, A., van de Riet, R.P.: WordNet++: a lexicon for the color-X method. Data Knowl. Eng. 38(1), 3–29 (2001)
El-Ghalayini, H., Odeh, M., McClatchey, R.: Engineering conceptual data models from domain ontologies: a critical evaluation. Int. J. Inf. Technol. Web Eng. 2(1), 57–70 (2006)
Embley, D.: Toward semantic understanding: an approach based on information extraction ontologies. In: Proceedings of the 15th Australian Database Conference, Denedin, New Zealand, pp. 3–12 (2004)
Evermann, J., Wand, Y.: Towards ontologically-based semantics for UML constructs. In: Kunii, H.S., Jajodia, S., Sølvberg, A. (eds.) ER 2001. LNCS, vol. 2224, pp. 354–367. Springer, Heidelberg (2001)
Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)
Fill, H.-G., Karagiannis, D.: On the conceptualization of modelling methods using the ADOxx meta modeling platform. Enterp. Model. Inf. Syst. Archit. 8(1), 4–25 (2013)
Fonseca, F., Martin, J.: Learning the differences between ontologies and conceptual schemas through ontology-driven information systems. JAIS – J. Assoc. Inf. Syst. Spec. Issue Ontol. Context IS 8(2), 129–142 (2007)
Fowler, M.: Analysis Patterns: Reusable Object Models. Addison Wesley, Menlo Park (1997)
Gailly F., Poels, G.: Conceptual modeling using domain ontologies: improving the domain-specific quality of conceptual schemas. In: Proceedings of the 10th Workshop on Domain-Specific Modeling, pp. 18–24 (2010)
Gogolla, M., Hohenstein, U.: Towards a semantic view of an extended entity-relationship model. ACM Trans. Database Syst. 16(3), 369–416 (1991)
Conesa, J., Storey, V., Sugumaran, V.: Usability of upper level ontologies: the case of ResearchCyc. Data Knowl. Eng. 69(4) (2010)
Gnesi, S., Fabbrini, F., Fusani, M., Trentanni, G.: An automatic tool for the analysis of natural language requirements. informe técnico, CNR Information Science and Technology Institute, pp. 53–62 (2004)
Han, T., Purao, S., Storey, V.: Generating large-scale repositories of reusable artifacts for conceptual design of information systems. Decis. Support Syst. 45, 665–680 (2008)
Harmain, M., Gaizauskas, R.: CM-builder: a natural language-based CASE tool for OO analysis. J. Autom. Softw. Eng. 10(2), 157–181 (2003)
Hartmann, S., Link, S.: English sentence structures and EER modeling. In: Proceedings of the 4th Asia-Pacific Conference on Conceptual Modeling (2007)
Hay, D.C.: Data Model Patterns: Conventions of Thought. Dorset House Publishing, New York (1996)
Jarvenpaa, S.L., Machesky, J.J.: Data analysis and learning: an experimental study of data modeling tools. Int. J. Man Mach. Stud. 31(4), 367–391 (1989)
Kim, N., Lee, S., Moon, S.: Formalized entity extraction methodology for changeable business requirements. J. Inf. Sci. Eng. 24, 649–671 (2008)
Kim, Y., March, S.: Comparing data modeling formalisms. Commun. ACM 38(6), 103–115 (1995)
Kop, C., Fliedl, G. Mayr, H.: From natural language requirements to a conceptual model. In: Proceeding of the First International Workshop on Evolution Support for Model-Based Development and Testing (EMDT2010), pp. 67–73 (2010)
Lenat, D.B.: CYC: a large-scale investment in knowledge infrastructure. Commun. ACM 38(11), 33–38 (1995)
Luisa, M., Mariangela, F., Pierluigi, N.I.: Market research for requirements analysis using linguistic tools. Requirements Eng. 9(1), 40–56 (2004)
Mala, A., Uma, V.: Automatic construction of object oriented design models [UML diagrams] from natural language requirements specification. In: Proceedings of the 9th Pacific Rim international conference on Artificial intelligence (PRICAI 2006), pp. 1155–1159 (2006)
Mascardi, V., Cordì, V., Rosso, P.: A comparison of upper ontologies. Technical report DISI-TR-06-2 (2007)
Mich, L., Garigliano, R.: The NL-OOPS project: object oriented modeling using the natural language processing system LOLITA. In: Proceedings of the 4th International Conference on the Applications of Natural Language to Information Systems (NLDB 1999) (1999)
Miller, G.A.: WordNet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)
Miyoshi, H., Sugiyama, K., Kobayashi, M., Ogino, T.: An overview of the EDR electronic dictionary and the current status of its utilization. In: Proceedings of the 16th International Conference on Computational Linguistics (1996)
Modha, D.S., Ananthanarayanan, R., Esser, S.K., Ndirango, A., Sherbondy, A.J., Singh, R.: Cognitive computing. Commun. ACM 54(8), 62–71 (2011)
Moody, D.L.: Metrics for evaluating the quality of entity relationship models. In: Ling, T.W., Ram, S., Lee, M.L. (eds.) ER 1998. LNCS, vol. 1507, pp. 211–225. Springer, Heidelberg (1998)
Moody, D.L., Shanks, G.G.: What makes a good data model? Evaluating the quality of entity relationship models. In: Loucopoulos, P. (ed.) ER 1994. LNCS, vol. 881, pp. 94–111. Springer, Heidelberg (1994)
Moody, D.L., Shanks, G.G.: Improving the quality of data models: empirical validation of a quality management framework. Inf. Syst. 28(6), 619–650 (2003)
Neill, C., Laplante, P.: Requirement engineering: the state of the practice. IEEE Softw. 20(6), 40–45 (2003)
Omar, N,. Hanna, P., Mc Kevitt, P.: Heuristics-based entity-relationship modelling through natural language processing. In: Proceedings of the Fifteenth Irish Conference on Artificial Intelligence and Cognitive Science (AICS-04), pp. 302–313 (2004)
Paek, Y.K., Seo, J., Kim, G.C.: An expert system with case-based reasoning for database schema design. Decis. Support Syst. 18(1), 83–95 (1996)
Parson, J., Saunders, C.: Cognitive heuristics in software engineering: applying and extending anchoring and adjustment to artifact reuse. IEEE Trans. Softw. Eng. 30(12), 873–888 (2004)
Popescu, D., Rugaber, S., Medvidovic, N., Berry, D.M.: Reducing ambiguities in requirements specifications via automatically created object-oriented models. In: Martell, C. (ed.) Monterey Workshop 2007. LNCS, vol. 5320, pp. 103–124. Springer, Heidelberg (2008)
Purao, S., Storey, V.C.: A multi-layered ontology for comparing relationship semantics in conceptual models of databases. J. Appl. Ontol. 1(1), 117–139 (2005)
Simsion, G.: Data Modeling Theory and Practice. Technique Publications, LLC, New York (2007)
Soares, A., Fonseca, F.: Ontology-Driven Information Systems at Development Time. IJCSS – J. Comput. Syst. Signals 8(2) (2007)
Song, I.-Y., Evans, M., Park, E.: A comparative analysis of entity-relationship diagrams. J. Comput. Softw. Eng. 3(4), 427–459 (1995)
Song, I.-Y., Yano, K., Trujillo, J., Lujan-Mora, S.: A taxonomic class modeling methodology for object-oriented analysis. In: Krostige, T.H.J., Siau, K. (eds.) Information Modeling Methods and Methodologies. Advanced Topics in Databases Series, pp. 216–240. Idea Group Publishing, Hershey (2004)
Sprinkle, J., Rumpe, B., Vangheluwe, H., Karsai, G.: Metamodeling - state of the art and research challenges. In: Giese, H., Karsai, G., Lee, E., Rumpe, B., Schätz, B. (eds.) MBEERTS. LNCS, vol. 6100, pp. 57–76. Springer, Heidelberg (2008)
Storey, V.C.: Classifying and comparing relationships in conceptual modeling. IEEE Trans. Knowl. Data Eng. 17(11), 1–13 (2005)
Storey, V.C.: Understanding semantic relationships. VLDB J. 2, 455–488 (1993)
Storey, V.C., Chiang, R., Goldstein, R., Dey, D., Sundaresan, S.: Database design with common sense business reasoning and learning. ACM Trans. Database Syst. 22(4), 471–512 (1997)
Thalheim, B.: Entity-Relationship Modeling: Foundations of Database Technology. Springer, Berlin (2000)
Thonggoom, O., Song, I.-Y., An, Y.: EIPW: a knowledge-based database modeling tool. In: Salinesi, C., Pastor, O. (eds.) CAiSE Workshops 2011. LNBIP, vol. 83, pp. 119–133. Springer, Heidelberg (2011)
Thonggoom, O., Song, I.-Y., An, Y.: Semi-automatic conceptual data modeling using entity and relationship instance repositories. In: Jeusfeld, M., Delcambre, L., Ling, T.-W. (eds.) ER 2011. LNCS, vol. 6998, pp. 219–232. Springer, Heidelberg (2011)
Topi, H., Ramesh, V.: Human factors research on data modeling: a review of prior research, an extended framework and future research directions. J. Database Manag. 13, 3–15 (2002)
Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, Los Altos (2005)
Zeng, Y.: Recursive object model (ROM)-modeling of linguistic information in engineering design. J. Comput. Ind. 59, 612–625 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Song, IY., Zhu, Y., Ceong, H., Thonggoom, O. (2015). Methodologies for Semi-automated Conceptual Data Modeling from Requirements. In: Johannesson, P., Lee, M., Liddle, S., Opdahl, A., Pastor López, Ó. (eds) Conceptual Modeling. ER 2015. Lecture Notes in Computer Science(), vol 9381. Springer, Cham. https://doi.org/10.1007/978-3-319-25264-3_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-25264-3_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25263-6
Online ISBN: 978-3-319-25264-3
eBook Packages: Computer ScienceComputer Science (R0)