Fact Based Modeling (FBM)

Fact-Based Modeling (FBM) is an approach to data modeling that focuses on capturing and organizing the essential facts about a domain, rather than defining the structure and relationships of data in terms of traditional database schema, such as tables and columns. FBM is based on the principles of formal logic and set theory, and it provides a more natural and intuitive way of representing the semantics of the problem domain.

FBM is particularly useful for conceptual modeling, as it allows analysts, designers, and subject matter experts to collaborate and define the business rules and requirements without getting bogged down in the technical details of database design. Some of the key concepts and components of Fact-Based Modeling include:

  1. Fact types: Fact types are the basic building blocks of FBM. A fact type is a statement that expresses a relationship between one or more objects or concepts in the domain. Fact types can be binary (involving two objects), ternary (involving three objects), or higher arity (involving more objects). For example, a binary fact type might be "Customer places Order," where "Customer" and "Order" are the objects involved.
  2. Object types: Object types represent the entities or concepts in the domain, such as people, organizations, products, or events. Object types can have attributes (e.g., name, address, price) and can participate in one or more fact types.
  3. Constraints: Constraints are rules that restrict the possible combinations of objects in a fact type. They can be used to enforce business rules, ensure data integrity, and maintain consistency within the model. Examples of constraints include uniqueness constraints (e.g., each customer must have a unique email address) and mandatory role constraints (e.g., every order must have a customer).
  4. Derived facts: Derived facts are facts that can be inferred or calculated from other facts in the model. They are not stored explicitly in the database but can be derived through logical inference or computation. For example, if we have facts about a customer's orders and the total amount of each order, we can derive the total amount spent by the customer.

Fact-Based Modeling offers several advantages over traditional data modeling techniques:

  1. Semantics: FBM focuses on capturing the meaning and semantics of the problem domain, making it easier for stakeholders to understand and agree on the requirements and business rules.
  2. Flexibility: FBM models can be easily extended and adapted as the domain and requirements evolve, without requiring major changes to the underlying database schema.
  3. Independence: FBM models are independent of any specific database technology or implementation, allowing for greater flexibility in choosing the appropriate storage and retrieval mechanisms.
  4. Formalism: FBM is based on a solid foundation of formal logic and set theory, providing a rigorous and consistent framework for modeling complex domains.

In summary, Fact-Based Modeling is an approach to data modeling that emphasizes the capture and organization of essential facts about a domain. It offers a more natural and intuitive way of representing the semantics of the problem domain, and provides a flexible and adaptable foundation for database design and implementation.