Universal Hex
Taxonomy
The Universal Hex Taxonomy (UHT) introduces a 32-bit semantic encoding framework that captures the essential traits of any entity — physical, functional, abstract, or social — in a fixed-length binary code. Each bit corresponds to one of 32 clearly defined properties, producing a compact semantic fingerprint. UHT enables precise comparisons via Hamming distance, supports clustering, and remains accessible to both humans and machines.
01 Introduction
No existing system combines universal scope, compactness, and interpretability. Domain-specific taxonomies lack flexibility, ontologies become unwieldy, and neural embeddings offer little transparency. UHT fills this gap with a simple fixed-length code built from binary traits organized into four layers: Physical, Functional, Abstract, and Social.
Every object, concept, or system can be tagged, compared, and understood using the same format. The result is a compact code that captures important characteristics while remaining explainable.
02 Structure & Layers
Each UHT code consists of 32 bits divided into four groups of eight. These correspond to four semantic layers:
Bit Layout
| Bit Range | Layer | Description |
|---|---|---|
| 1–8 | Physical | Tangibility, materiality, form |
| 9–16 | Functional | Purpose, behavior, operation |
| 17–24 | Abstract | Symbolism, logic, structure |
| 25–32 | Social | Culture, regulation, identity |
Each number maps to a trait. Group the bits into four bytes and convert to hexadecimal for
readability. The result is an 8-character hex string like CE880000.
Converting Bits to Hex
Example: encoding a Paperclip.
To decode, reverse these steps: split the hex into byte pairs, convert to binary, and match each bit to its corresponding trait.
03 Trait Reference
Each of the 32 bits corresponds to a named property. Bits are either on (1) or off (0). Below is the complete reference with edge cases from the classification specification.
Physical Layer · Bits 1–8
| Bit | Trait | Description |
|---|---|---|
| 1 | Physical Object | A discrete, bounded physical entity that occupies space and has tangible form. |
| 2 | Synthetic | Created, manufactured, or significantly shaped by human activity or intention. |
| 3 | Biological/Biomimetic | Has biological origin or structure inspired by biology. |
| 4 | Powered | Requires external energy input to operate or perform its primary function. |
| 5 | Structural | Serves a load-bearing, shape-maintaining, or structural integrity function. |
| 6 | Observable | Can be directly detected by human senses or scientific instruments. |
| 7 | Physical Medium | Composed of physical matter — has substance and mass. |
| 8 | Active | Exhibits autonomous behavior or initiates actions independently. |
Edge cases — Physical Layer
Functional Layer · Bits 9–16
| Bit | Trait | Description |
|---|---|---|
| 9 | Intentionally Designed | Created or adapted with a deliberate purpose or intended function. |
| 10 | Outputs Effect | Actively produces measurable outputs: light, sound, force, heat, or information. |
| 11 | Processes Signals/Logic | Interprets, transforms, routes, or computes data, signals, or logical operations. |
| 12 | State-Transforming | Can change its own internal state or configuration based on inputs or time. |
| 13 | Human-Interactive | Designed to be directly used, operated, or engaged with by humans. |
| 14 | System-Integrated | Operates as part of a larger system or network; function depends on context. |
| 15 | Functionally Autonomous | Operates independently without requiring continuous external control. |
| 16 | System-Essential | Critical to a system’s operation — removal would cause failure or degradation. |
Edge cases — Functional Layer
Abstract Layer · Bits 17–24
| Bit | Trait | Description |
|---|---|---|
| 17 | Symbolic | Represents concepts through signs, models, or conventional meaning. |
| 18 | Signalling | Actively transmits or encodes information through signals or media. |
| 19 | Rule-Governed | Behavior or structure defined by formal rules, algorithms, or logical systems. |
| 20 | Compositional | Structured in meaningful layers, modules, or hierarchical components. |
| 21 | Normative | Directs, guides, or constrains behavior through rules or expectations. |
| 22 | Meta | Refers to itself, its category, or the conceptual structures that define it. |
| 23 | Temporal | Time plays a defining role in identity, structure, or effect. |
| 24 | Digital/Virtual | Exists primarily in digital form, as data, software, or virtual representation. |
Edge cases — Abstract Layer
04 Classification Methodology
UHT classification uses a strict, minimalist approach. Each of the 32 traits is evaluated independently against the entity under consideration.
Inclusion Standard: A trait should be marked Included (1) only if it is intrinsically present in the entity’s identity. The trait must be:
- Structurally inseparable from the entity
- Functionally designed-in (part of its purpose or operation)
- Logically entailed by its construction or symbolic role
Exclusion Rule: A trait should be marked Excluded (0) if it is merely attributed in context, present through metaphor, or not essential to the entity’s core identity.
Avoid Trait Inflation: Do not include traits based on secondary usage, surrounding systems, or cultural interpretation — unless that role is intrinsically embedded in the entity’s identity (e.g., a “Police Badge” is intrinsically symbolic and social).
Justification Requirement
For each of the 32 traits, the classifier must indicate whether it is Included or Excluded and provide a concise justification based on the official trait definitions. This ensures auditability and reproducibility across classifiers.
Automated Classification Pipeline
The UHT Factory uses an LLM-driven classification engine:
- Cache check — Redis lookup by entity name
- Parallel trait evaluation — 32 async tasks sent to an LLM, each evaluating one trait
- UHT code construction — 32-bit binary string converted to 8-character hex
- Storage — Redis cache + Neo4j graph database
Each trait evaluation produces a JSON object with applicable (boolean),
confidence (0.0–1.0), and justification (max 100 words).
05 Encoding Guide
Encoding Workflow
- Evaluate all 32 traits using the official definitions
- Justify every inclusion/exclusion
- Build the 32-bit binary string (MSB = bit 1)
- Group into four 8-bit bytes (one per layer)
- Convert each byte to a 2-character hex pair
- Concatenate:
[PHYS][FUNC][ABST][SOC]
Decoding Workflow
- Split the 8-character hex code into four 2-character pairs
- Convert each pair to an 8-bit binary string
- Map each bit to its corresponding trait name
- Use the active traits for search, comparison, or explanation
Bit Ordering
Within each layer byte, Bit 1 (of that layer) corresponds to the Most Significant Bit (MSB, position 27). Bit 8 maps to the Least Significant Bit (LSB, position 20). This means the first trait in each layer controls the leftmost bit of that hex pair.
Output Format
06 Semantic Compression
UHT codes act as a form of semantic compression, reducing complex identity into 32 compact, interpretable bits. This encoding captures the essential meaning of an object or concept into a fixed-size representation.
Benefits
- Compactness — Each code is only 32 bits (8 hex characters), enabling efficient storage
- Speed — Bitwise operations like XOR and Hamming distance allow for fast comparisons
- Clarity — Each bit is linked to a clear trait, making encodings interpretable and auditable
Semantic Proximity via Hamming Distance
Comparing two UHT codes by their Hamming distance — the number of differing bits — reveals how semantically similar two entities are. The more bits they share, the closer they are in meaning.
| Entity A | Code | Entity B | Code | Distance |
|---|---|---|---|---|
| Mechanical Clock | DEF42205 | Digital Alarm Clock | DEF82205 | 2 |
| Coffee Machine | DEFA2205 | Water Filtration Unit | DFD60205 | 5 |
| Paperclip | D78800C5 | National Anthem | 0080C9FF | 18 |
Unlike neural embeddings or black-box classification systems, UHT codes remain human-readable. Every trait is explicit. Differences between entities can be directly traced to the bits that differ.
07 Worked Examples
A manufactured object that holds papers by shape. Recognized universally as a basic office tool.
A modern sensor that interprets and reports temperature in regulated systems like healthcare and HVAC.
A timed signaling device for home or institutional use. Emits sound or light to mark events, widely understood in global culture.
08 Applications
UHT codes apply across diverse domains wherever structured comparison, discovery, or metadata is needed.
09 API Reference
The UHT API is served at factory.universalhex.org/api/v1/. Interactive Swagger
documentation is available at
factory.universalhex.org/docs.
10 Comparison to Existing Approaches
UHT can be compared to several established methods for representing identity, meaning, or metadata.
| Method | Common Usage | Limitations | UHT Advantage |
|---|---|---|---|
| RDF / OWL Ontologies | Semantic web, linked data | Schema-heavy, domain-specific | One format usable across all domains |
| Neural Embeddings | Machine learning, NLP | Opaque, unstable, hard to explain | Transparent, fixed-length, human-readable |
| ISO Metadata Standards | Documentation, archiving | Rigid, verbose, hard to compare | Compact, trait-based, easy to cluster |
| Feature Flags / Tags | Software configs, taxonomies | Flat, unstructured, lacks depth | Layered structure and formal bit encoding |
UHT stands out by offering a hybrid: a fixed-length, interpretable code that is small enough to fit anywhere but expressive enough to work across physical, abstract, and social contexts.
Social Layer · Bits 25–32
Edge cases — Social Layer