A Relational Model of Data for Large Shared Data Banks.

Codd, E. F. (1970). A Relational Model of Data for Large Shared Data Banks. ACM, 13(6), 377-387.

Type

Journal article

Intellectual base

Primary research

Year

1970

Volume

13

Issue

6

Pages

377-387

DOI

10.1145/362384.362685

DOI registrant

Association for Computing Machinery

Link

https://doi.org/10.1145/362384.362685

Cited from

computer_science, engineering_design, information_theory, literature_literary_theory, mathematics, physics, statistics_experimental_design, systems_cybernetics

Cited by

17 citations across 17 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Compression

  • This sourceFounds the relational data model. DOI verified.

• Data Integrity

  • This sourceIntroduces the relational model and the notion of declared integrity constraints over relations.

• Denormalization
  • The prime is the trade: one accepts a synchronization burden, in which every duplicated fact must be kept in sync as the underlying truth changes

    This sourceFoundational paper introducing the relational model and normalization, defining the canonical form against which denormalization re-introduces controlled redundancy.

    Supported in partVerified against the publisher's abstract

    Codd's abstract introduces the normal form for database relations and treats redundancy and consistency as problems in the user's model, backing only the claim's vocabulary-provenance half, not the cross-domain trade framing.

    “A model based on n -ary relations, a normal form for data base relations, and the concept of a universal data sublanguage are introduced.”

    Read by an automated reader; not a human review. How support was checked

• Discrete vs. Continuous (Quantization)

  • This sourceFounds the relational data model over discrete n-ary relations.

• Fabula And Syuzhet
  • The pattern instantiates the broader underlying-versus-presented duality: logical schema versus physical schema, abstract syntax tree versus source text, model versus view, semantics versus surface form, signal versus encoding.

    This sourceEstablishes the logical schema as independent of physical storage/views — the schema-versus-view instance of the underlying-versus-presented separation.

    Supported in partVerified against the publisher's abstract

    Codd's abstract states data independence for internal vs external representation, supporting only the schema/view instance of the claim, not the other four dualities.

    “Activities of users at terminals and most application programs should remain unaffected when the internal representation of data is changed and even when some aspects of the external representation are changed.”

    Read by an automated reader; not a human review. How support was checked

• Measurement Uncertainty and Observational Noise
  • Listed in the references but not attached to a specific claim.
• Multiplexing
  • Listed in the references but not attached to a specific claim.
• Projection
  • In databases the select operation is literally called projection in relational algebra — drop the columns not in the target, keep the rows.

    This sourceDefines the relational model whose projection operation drops attributes not in the target.

• Redundancy
  • Listed in the references but not attached to a specific claim.
• Relation
  • Arity is part of the relation's identity; changing it produces a different relation
• Set and Membership
  • In predicate logic, sets are the extensions of predicates and the domains of quantification: every formula "for all x in S, P(x)" presumes a set S. In relational databases
• Signal Decay and Fadeout
  • Listed in the references but not attached to a specific claim.
• Transaction
  • Listed in the references but not attached to a specific claim.

Domain-specific

• Data Model
  • Codd's relational model introduced relations, operations, and integrity concerns while separating logical representation from machine organization.

Mechanisms

• Database View or Entity Projection
  • Its strength is logical data independence: one authoritative base, many aspect-shaped windows, none of which can drift because none stores its own copy.

    This sourcePresents the relational model as a basis for data independence and defines projection for deriving relations from other relations.

• Foreign-Key Constraint
  • It is the textbook enforcement of referential integrity from the relational model.

    This sourceDefines foreign keys within the relational model as references to primary keys in related relations.

• Predicate Satisfaction Filter
  • Its strength is transparency: the membership rule is written down, applied uniformly, and open to challenge — a selection predicate in the relational-algebra sense

    This sourceDefines relational selection as deriving a relation by retaining tuples that satisfy a specified predicate.

Verification

Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.

Does it back the claim? Read against the text for 2 of 17 citations: 2 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.

Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.

See how references were verified.

Registry ID ref:2ac7b29ada60 · see in the full table