Peter P. Chen

The entity-relationship model: toward a unified view of data

A data model, called the entity-relationship model, which incorporates the semantic information in the real world is proposed. A special diagramatic technique is introduced for exhibiting entities and relationships. An example of data base design and description using the model and the diagramatic technique is given. The implications on data integrity, information retrieval, and data manipulation are discussed.

English sentence structure and entity-relationship diagrams

Abstract In many information system projects, information requirements are initially documented in English, and then database designers convert these English descriptions into database schemas in terms of entity-relationship (ER) diagrams (or other similar representations). This paper studies the correspondence between English sentence structure and ER diagrams, and proposes eleven rules for translation. The basic constructs of English, such as noun, verb, adjective, adverb, gerund, and clause, are found to have counterparts in the ER diagrammatic technique. Finally, an example is used to demonstrate the applicability of these rules in database design.

Entity — Relationship modeling and fuzzy databases

This work describes an integration of an entity/relationship model and fuzzy databases. It outlines a formal model for representing fuzziness in the ER model, and sketchs a version of the ER algebra, adapted to manipulating fuzzy databases.

Advances in Conceptual Modeling

Traditionally product data and their evolving definitions, have been handled separately from process data and their evolving definitions. There is little or no overlap between these two views of systems even though product and process data arc inextricably linked over the complete software lifecycle from design to production. The integration of product and process models in an unified data model provides the means by which data could be shared across an enterprise throughout the lifecycle, even while that data continues to evolve. In integrating these domains, an object oriented approach to data modelling has been adopted by the CRISTAL (Cooperating Repositories and an Information System for Tracking Assembly Lifecycles) project. The model that has been developed is description-driven in nature in that it captures multiple layers of product and process definitions and it provides object persistence, flexibility, reusability, schema evolution and versioning of data elements. This paper describes the model that has been developed in CRISTAL and how descriptive meta-objects in that model have their persistence handled. It concludes that adopting a description-driven approach to modelling, aligned with a use of suitable object persistence, can lead to an integration of product and process models which is sufficiently flexible to cope with evolving data definitions. Ke)fwords: Description-Driven systems. Modelling change, schema evolution, versioning

The entity-relationship model: a basis for the enterprise view of data

The concept of the enterprise view of data is very useful in the database design process and in the construction of conceptual schema. This paper discusses the use of the entity-relationship approach in describing and maintaining the enterprise view of data. Fundamental operations for changing the enterprise schema are presented. Finally, an example is given to show the differences between the entity-relationship approach and the data-structure approach in modeling the enterprise view of data.

Entity-relationship modeling: historical events, future trends, and lessons learned

This paper describes the historical developments of the Entity-Relationship (ER) model from the 1970s to recent years. It starts with a discussion of the motivations and environmental factors in the early days. Then, the paper points out the role of the ER model in the Computer-Aided Software Engineering (CASE) movement in the late 1980s and early 1990s. It also describes the possible role of the authors Chinese cultural heritage in the development of the ER model. In that context, the relationships between natural languages (including Ancient Egyptian hieroglyphics) and ER concepts are explored. Finally, the lessons learned and future directions are presented.

An analysis of additivity in OLAP systems

Accurate summary data is of paramount concern in data warehouse systems; however, there have been few attempts to completely characterize the ability to summarize measures. The sum operator is the typical aggregate operator for summarizing the large amount of data in these systems. We look to uncover and characterize potentially inaccurate summaries resulting from aggregating measures using the sum operator. We discuss the effect of classification hierarchies, and non-, semi-, and fully- additive measures on summary data, and develop a taxonomy of the additive nature of measures. Additionally, averaging and rounding rules can add complexity to seemingly simple aggregations. To deal with these problems, we describe the importance of storing metadata that can be used to restrict potentially inaccurate aggregate queries. These summary constraints could be integrated into data warehouses, just as integrity constraints and are integrated into OLTP systems. We conclude by suggesting methods for identifying and dealing with non- and semi- additive attributes.

Data warehouse design to support customer relationship management analyses

CRM is a strategy that integrates the concepts of Knowledge Management, Data Mining, and Data Warehousing in order to support the organizations decision-making process to retain long-term and profitable relationships with its customers. In this paper, we first present the design implications that CRM poses to data warehousing, and then propose a robust multidimensional starter model that supports CRM analyses. We then present sample CRM queries, test our starter model using those queries and define two measures (% success ratio and CRM suitability ratio) by which CRM models can be evaluated. We finally introduce a preliminary heuristic for designing data warehouses to support CRM analyses. Our study shows that our starter model can be used to analyze various profitability analyses such as customer profitability analysis, market profitability analysis, product profitability analysis, and channel profitability analysis.

An algebra for a directional binary entity-relationship model

There are many versions of Entity-Relationship (ER) Models. This paper proposes an algebra for a binary ER model with directional relationships. The proposed algebra can be used as the basis of a data manipulation language for an ER database management system.

Suggested research directions for a new frontier – active conceptual modeling

This paper discusses several research directions and challenges of a new frontier of research: active conceptual modeling. It suggests how the Entity-Relationship (ER) model may be extended to satisfy some of the needs of a new set of emerging user needs and applications.