Data Structures
The study of ways to organise and store data in a computer so it can be accessed and modified efficiently.
A discipline is a lens, not an owner — the same idea can be viewed through many.
Concepts viewed through this lens
These numbers describe the current Thinking OS knowledge slice, not the whole field.
Disciplines it bridges to
Each bridge is built by ideas the two fields share, the thinking patterns that recur across both, and a representative relationship that shows how they connect.
Data Structuresconnects toComputer Science
Shared thinking patterns
Why this bridge exists
Hash table depends on Hash function — hash table depends on hash function.
Explore this connection →Data Structuresconnects toMathematics
Shared concepts
Shared thinking patterns
Why this bridge exists
Algorithm is a Sequence — An algorithm is an ordered sequence of steps.
Explore this connection →Data Structuresconnects toBiology
Shared concepts
Shared thinking patterns
Why this bridge exists
Hierarchy is a Pattern — Hierarchy is a structural pattern of levels.
Explore this connection →Data Structuresconnects toDiscrete Mathematics
Shared concepts
Shared thinking patterns
Why this bridge exists
Algorithm is a Sequence — An algorithm is an ordered sequence of steps.
Explore this connection →Data Structuresconnects toAlgorithms
Shared thinking patterns
Why this bridge exists
Algorithm is a Sequence — An algorithm is an ordered sequence of steps.
Explore this connection →Data Structuresconnects toSoftware Engineering
Shared concepts
Shared thinking patterns
Why this bridge exists
Algorithm is a Sequence — An algorithm is an ordered sequence of steps.
Explore this connection →Data Structuresconnects toGraph Theory
Why this bridge exists
Edge is part of Graph data structure — Edges join the vertices of a graph.
Explore this connection →Data Structuresconnects toBioinformatics
Shared concepts
Shared thinking patterns
Why this bridge exists
DNA is a Sequence — DNA carries meaning as a sequence.
Explore this connection →
Field shape — representation health
67/100 overall · 10 concepts
The eight dimensions measure Thinking OS coverage of this field, not the quality or importance of the discipline.
What kind of structure is this field?
Interpreted from the current atlas — how this field is represented, not a judgement of the field.
Representation health 67/100 — healthy representation. Strongest: evidence, cross-disciplinary. Thinnest: factual depth.
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
Its 67 representation-health is above the 55 median of 225 similarly-sized disciplines (comparable by concept count).
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
67% of its relations reach into 22 other disciplines — an outward-facing field in the atlas.
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
Current atlas gaps: no equations stored.
atlas representation · Measures the current Thinking OS representation, not the quality or importance of the field.
40% of its concepts have a single connection (mean internal degree 1.4) — a fairly cohesive internal structure.
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
How this lens connects
The kinds of relationship that characterise this discipline lens in the current slice.
Coverage matrix
How these concepts distribute across domains and concept families — real counts, not a score.
Knowledge timeline
Real, sourced key dates of these concepts.
- 1953Hash table · Discovery · Computer Science
- 1955Linked list · Formalization · Computer Science
Ideas that connect this discipline outward
Concepts viewed through this lens that reach disciplines it does not itself carry — concept-level bridges (distinct from the discipline-to-discipline bridges below).
- SequencereachesAlgorithmsBiochemistryBiologyCell BiologyCognitive ScienceDesignEducationEducational ScienceEvolutionary BiologyGeneticsLogicMachine LearningSoftware EngineeringTheory of Computation
- HierarchyreachesCognitive ScienceDesignEducationEducational ScienceMachine LearningMathematicsProject Management
- Graph data structurereachesGraph TheoryManagementMathematicsProject Management
Mental models that recur here
Networks ×2
A set of parts connected so that a change in one can spread to others through the links.
Emergence ×1
When many simple parts interacting by simple rules produce a pattern or behaviour that none of the parts has on its own.
Information ×1
Anything that reduces uncertainty. It can be encoded into a signal, sent across a channel, and decoded — and noise can corrupt it on the way.
Recursion & self-similarity ×1
A thing defined in terms of smaller copies of itself — solve the small case and the same rule builds the whole, often looking similar at every scale.
People represented in this atlas
People tagged with this lens who have a recorded contribution. Not exhaustive, and not a ranking.
- Agner Krarup Erlang
1878–1929
- Herbert Simon
1916–2001
- Cliff Shaw
1922–1991
- Allen Newell
1927–1992
- Robert Tarjan
1948–present
- 10 concepts are viewed through this lens.
- 3 of them bridge into other disciplines.
- Its signature thinking pattern is “Networks” (recurs in 2 concepts).
- The most common kind of connection here is “Kind & structure”.
- It is most tightly linked to Computer Science.
Derived from the current graph structure — observations, not a judgement of the field.