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By E. F. Codd.

Primary source: db.dobo.sk/wp-content/uploads/2015/11/Codd_1970_A_relational_model.pdf

Abstract and sections 1.1–1.3, data independence and relations.

Data independence separates the logical meaning of stored data from details that an application need not know. Physical independence permits changing indexes, page layout or access paths without changing a query's meaning. Logical independence permits some changes in the database's logical organization while preserving the interface exposed to existing applications, often through views.

For example, a query asking for an employee's department should return the same answer after the database replaces a table scan with a B-tree index. An application that follows stored record addresses directly would instead depend on that representation. E. F. Codd's1970 relational model explicitly argued against dependencies on ordering, indexes and access paths.^[ref] Independence does not mean every schema change is invisible: removing a field an application needs changes its contract unless another representation supplies equivalent information.

E. F. Codd introduced the relational model in his 1970 paper on large shared data banks. Data is represented by relations rather than application-visible pointers and access paths, supporting data independence: changing physical organization need not change the meaning of a query.^[ref]

The distinction is operationally important. A query can request tuples satisfying a predicate while the system chooses an index or scan. Applications specify the information they need instead of navigating one fixed storage layout. Mathematical relations also expose dependencies among attributes, providing a foundation for database normalization.

The relational model represents data as database relations, which are sets of database tuples over specified value domains. A relational schema names the database attributes and states database integrity constraints; an instance supplies their current values. Relational algebra describes operations on this logical data, while storage order, indexes and access paths belong to its implementation.

For example, the database relation Reading(sample, value) can contain $(A,3),(B,8)$. A relational selection for values above five followed by relational projection onto sample identifiers returns $\{B\}$. Changing the underlying file layout or adding an index need not change that query's meaning. Mathematical database relations have set semantics; SQL often uses bag semantics and has additional SQL NULL behavior.

In his 1970 paper, E. F. Codd argued for data independence: application logic should not rely on particular stored orderings, indexes or navigational paths. His relational formulation made that separation central to database design.^[ref]