Data Models are used to define the data needed for an Information system to use and/or control, and often form the basis for the definition and creation of databases. The most common format used to capture data requirements is the Entity-Relationship Diagram, which I believe originated with Clive Finkelstein and was most popularized by James Martin’s Information Engineering Methodology.
A Web Search on Entity-Relationship Diagrams or on Data Models will return thousands of hits, as I think that Data Models as a requirements format are more popular than even Use Cases. Here are two interesting links I found today:
1) Data Modeling: Finding the Perfect Fit
An Introduction to Data Modeling
by Tim McLellan
Copyright 1995. All Rights Reserved.
2) Applied Information Science
(Data) Modeling Methodologies
In my use of data models for Requirements, the main component is the Data Entity, a subject of interest to the Business, associated by the business relationships between them. Each entity contains data items/attributes that relate to or describe the Entity. Each attribute belongs only to one Entity, so duplication of Requirements is reduced.
Entity-Relationship data models are also commonly classified as ‘Conceptual’ or ‘Logical’, in that they are intended to communicate the data requirements of the Business. Such models can then be transformed into a ‘Physical’ Data Model that is used to design a database.
If a Data Model is used in conjunction with Use Cases, the latter’s data items can be defined by a cross-reference to the Data Model. As a result, a data item used in multiple use cases will be defined only once, eliminating duplication and inconsistency.