A Conceptual View of Data for Decision-Oriented Databases: A Knowledge-Driven Approach

Authors

Sung-kwan Kim, University of Arkansas at Little RockFollow
Wenjun Wang, University of Arkansas at Little RockFollow
Seunghyun Kim, University of Arkansas at Little RockFollow

Document Type

Article

Abstract

Typical database design goes through three levels of data modeling: conceptual modeling, logical modeling, and physical modeling. In particular, conceptual modeling is important since it captures and documents user data requirements. Conceptual modeling serves as a blueprint for designing a database by defining information content to be included in a database. Presently, decision-oriented databases have no well-accepted conceptual modeling approach to apply. While some use conceptual modeling approaches for transaction-oriented databases such as the ER (Entity-Relationship) model, they are not well-suited for decision-oriented databases. It is hard to map from the ER Model to decision-oriented data models. Others attempt to address the challenges through unified data models, automated tools, and best practices, but it is still in need to develop more robust, standardized conceptual models that can accommodate the unique characteristics of decision-oriented data structures. In this paper, we propose a new approach to conceptual modeling for decision-oriented databases. This approach is knowledge-driven and decision-oriented. It provides a comprehensive view of data at the conceptual level for decision-oriented databases.

Recommended Citation

Kim, Sung-kwan; Wang, Wenjun; and Kim, Seunghyun (2025) "A Conceptual View of Data for Decision-Oriented Databases: A Knowledge-Driven Approach," Journal of International Technology and Information Management: Vol. 33: Iss. 1, Article 7.
DOI: https://doi.org/10.58729/1941-6679.1599
Available at: https://scholarworks.lib.csusb.edu/jitim/vol33/iss1/7