Peter Chen

Peter Chen's ER model is the first major and most widely used conceptual model in data modeling, software engineering, and information systems development. Dr. Chen developed the translation algorithms from the ER model to the relational database (DB) model, which subsequently has served as the basis for relational DB design methodologies and tools. He also developed tools and algorithms for reverse-engineering COBOL data structures and database schemas into ER diagrams. In many organizations all over the world, ER modeling and relational DBs are two major pillars of supporting daily operations and decision-making. It is difficult to imagine how the world could still process and integrate smoothly such large amounts of data as we have been doing every day without these two major pillars.

Dr. Chen is one of the pioneers of CASE methodologies and tools. He led a programming team developing some of early commercial CASE tools, which were adopted as corporate standards for EXXON and AT&T. He was one of the two keynote speakers of the first major CASE Symposium (Atlanta, 1988). Since then, he has given more than 25 keynote speeches on various topics in software developments.

Entity and relationship concepts are very fundamental in describing our perceptions of the world, which are crucial in modeling the world and user requirements. However, in the past, most people used these concepts informally. Chen was the first to develop rigorous mathematical formulations and widely accepted graphic notations of the entity/relationship concept. He also developed a design methodology and translation rules/simpler-algorithms that create the "best" relational database design (i.e., to derive the 3rd normal form tables/relations as advocated by Codd) without executing complicated and lengthy mathematical normalization algorithms.

The ER model will continue to influence us in the foreseeable future because its main concepts have been adopted by object-oriented analysis and design methodologies, UML, webpage design, XML, and data modeling for bioinformatics.