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Data store

A persistent repository and access boundary for collections of data, encompassing databases, files, object stores and other managed storage forms.

Version
v1 · 2026-09-08 · History
Domain-specific #
4040
Origin domain
information systems
Subdomain
information systems

Core Idea

The term is broader than database and can denote a logical repository in data-flow modeling or a physical service; durability, consistency and access semantics must be stated. Data is serialized into a managed medium, identifiers and structure support later retrieval and update and lifecycle rules preserve or delete records across process restarts. The abstraction is therefore identified by a declared carrier, a transformation or constraint over that carrier, and an invariant that tells an analyst whether the named structure is genuinely present.

Scope of Application

Data store belongs to information systems and is useful where the analyst can specify the typed information systems carrier, including objects, relations, parameters, conventions, evidence, boundaries, and comparison targets, then evaluate the data collection and schema, logical or physical boundary, storage medium and format, identifiers and indexing, read write and query interface, durability and consistency, concurrency, retention backup and access controls are explicit. The scope is broad within that domain but bounded by the need for the data collection and schema, logical or physical boundary, storage medium and format, identifiers and indexing, read write and query interface, durability and consistency, concurrency, retention backup and access controls are explicit.

Clarity

The abstraction clarifies a crowded vocabulary by making the data collection and schema, logical or physical boundary, storage medium and format, identifiers and indexing, read write and query interface, durability and consistency, concurrency, retention backup and access controls are explicit the center of the account. A claim should name the carrier, the governing operation or relation, the applicable assumptions, and the recognition test.

Manages Complexity

Without the abstraction, an analyst must reason directly over many local details: the carrier roles, admissibility assumptions, competing conventions, derived invariants, boundary cases, and proof or validation obligations specific to Data store. Data store compresses them into the roles in the structural signature. That compression permits comparison across instances without erasing the variables that determine validity. It also exposes which details may be varied safely and which are constitutive.

Abstract Reasoning

  1. Identify the carrier. State what the elements, states, objects, or observations are: the typed information systems carrier, including objects, relations, parameters, conventions, evidence, boundaries, and comparison targets. Reject examples whose alleged carrier belongs to a different problem. 2. Lock the constitutive rule. Express the data collection and schema, logical or physical boundary, storage medium and format, identifiers and indexing, read write and query interface, durability and consistency, concurrency, retention backup and access controls are explicit independently of one notation or implementation.

Knowledge Transfer

Knowledge transfers strongly among subfields of information systems because they reuse the typed information systems carrier, including objects, relations, parameters, conventions, evidence, boundaries, and comparison targets, Data is serialized into a managed medium, identifiers and structure support later retrieval and update and lifecycle rules preserve or delete records across process restarts., and type the carrier, state every parameter and convention in the definition, test that the data collection and schema, logical or physical boundary, storage medium and format, identifiers and indexing, read write and query interface, durability and consistency, concurrency, retention backup and access controls are explicit, compare the nearest accepted identity, and report counterexamples, uncertainty, and limiting cases.

Relationships to Other Abstractions

Local relationship map for Data storeParents appear above the current abstraction, mutual partners to the right, and children below. Node labels state whether each abstraction is prime or domain-specific; colors identify relation types.Data storeDOMAINPrime abstraction: Data Structure — is a kind ofData StructurePRIME

Current abstraction Data store Domain-specific

Parents (1) — more general patterns this builds on

  • Data store is a kind of Data Structure Prime

    The proposed strict upward parent is prime:data_structure.

Hierarchy path (1) — routes to 1 parentless root

Neighborhood in Abstraction Space

Data store sits in a crowded region of the domain-specific corpus (7th percentile for distinctiveness): several abstractions share nearly its structure, so a description that fits it tends to fit its neighbors too.

Family — Knowledge Organization & Retrieval (39 abstractions)

Nearest neighbors

Computed from structural-signature embeddings · 2026-09-08