Information
Anything that reduces uncertainty; it can be encoded, sent and decoded.
At a glance
Key signals
22% cross fields · reaches 8 more
- Information Theory
- Computer Science
- Biology
- Explanation
- Examples
- Misconception
- Sourced relations 6
- Attribution
Dependencies
What this concept builds on and what it makes possible — derived from the atlas’s dependency, causal and structural relations, not from every related edge.
Foundations · builds on
SignalenablesInformationEstablished
A signal carries information across a channel.
Mechanism: Information needs a physical carrier — a sound, a light pulse, a voltage — that varies in a way the receiver can read.
- A Mathematical Theory of Communication (1948) verified
System context
Datais aInformationEstablished
data is a kind of Information.
Mechanism: Data becomes information when it is interpreted: raw values gain meaning once placed in a context that a person or program can use.
- Wikidata verifiedmoderate evidence
Mass mediais part ofInformationEstablished
Media carry information.
Mechanism: Mass media are society's large-scale channels for distributing information to dispersed audiences.
Structural role & consequence
Interpreted from the current atlas graph — what the connections mean, not just how many there are.
Removing this node severs the only sampled structural route between Information science and Journalism — a non-redundant bridge here.
structural · Structural removal simulation — not a historical or causal counterfactual.
22% of its relationships cross field boundaries, reaching 8 other disciplines — unusual in a discipline where most concepts stay within their field.
structural · Structural graph analysis — not a claim of importance, causation or history.
Currently dark in the atlas: no key date stored · 9 of 9 of its relations lack claim-level evidence.
atlas representation · Describes the current Thinking OS representation, not the state of the world.
Builds on 1 foundation (requires / depends-on / derived-from / emerges-from).
structural · Structural graph analysis — not a claim of importance, causation or history.
cross-field
7 within-field, 2 cross-field
Strengths & constraints
Constraints
- Evidence coverage currently thin in the atlas — few of its relationships carry claim-level evidence. atlas representation
- Non-redundant bridge — removing it severs a sampled route between neighbouring clusters. structural
- No dated history stored — the atlas records no key date for this concept. atlas representation
Conditions
- Its dependency reading rests on 1 foundation relation. structural
- Read structurally — most of its relationships carry no external evidence yet, so claims here are graph-derived. structural
Dependency radial
What this concept builds on (left) and what it makes possible (right) — derived from dependency and causal relations.
Seen through each discipline
How this concept sits in each of its fields — derived from its real connections in the graph, not asserted.
Through this lens it connects to Signal, Bit, Encoding and Error detection and correction.
Through this lens it connects to Data, Cryptography, Bit and Encoding.
Through this lens it connects to Signal, Mass media and Encoding.
Related ideas to explore
Concepts that look related but are not yet connected here — candidates for a connection to reason about, not established links.
This idea also appears in…
The same structure shows up in other disciplines. These are real recurrences drawn from the graph — a starting point for asking “what carries over, and what changes?”
Information34 disciplines · 27 concepts
Signal vs noise14 disciplines · 10 concepts
Concepts
shares a mental model · shares a mental model
shares a mental model · shares a mental model
shares a mental model
shares a mental model
shares a mental model
shares a mental model
Information is whatever tells you something you did not already know — it cuts down the possibilities. A message carries more information the more uncertainty it removes.
Mental models at work here
Information
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.
Ask: what did the receiver not know before, and what does the message let them rule out?
Signal vs noise
Real data mixes a meaningful pattern (signal) with random variation (noise); the skill is telling them apart before you act on either.
Ask how much of what you see could be chance. Small samples are mostly noise; averaging and repetition pull the signal out.
- Connects 9 other ideas across 4 disciplines.
- A cross-disciplinary bridge — its connections reach into 8 other fields.
- Most of its connections are of the “Teaching link” kind.
- It exercises 2 reusable thinking patterns.
Derived from the graph’s real structure — observations, not a score.
Sources
- A Mathematical Theory of Communication (1948) verified