Update collection card with individual dataset links

README.md

@@ -10,343 +10,63 @@ tags:
   - personality
   - affective-computing
   - mental-health
-  - nlp
-  - taxonomy
-  - affectively
-  - edgework
   - mindfulness
   - breathing
   - technical-mindfulness
-pretty_name: "Behavioral Taxonomy: Emotions, Loops, Biases, Traits & Mindfulness Techniques"
+  - affectively
+  - edgework
+  - collection
+pretty_name: "Behavioral Taxonomy Collection"
 size_categories:
   - 1K<n<10K
-dataset_info:
-  - config_name: emotions
-    features:
-      - name: id
-        dtype: string
-      - name: name
-        dtype: string
-      - name: level
-        dtype: string
-      - name: valence
-        dtype: string
-      - name: arousal
-        dtype: string
-      - name: description
-        dtype: string
-    splits:
-      - name: train
-  - config_name: behavioral_loops
-    features:
-      - name: id
-        dtype: int64
-      - name: name
-        dtype: string
-      - name: category_name
-        dtype: string
-      - name: given
-        dtype: string
-      - name: when
-        dtype: string
-      - name: then
-        dtype: string
-      - name: result
-        dtype: string
-    splits:
-      - name: train
-  - config_name: cognitive_biases
-    features:
-      - name: id
-        dtype: string
-      - name: name
-        dtype: string
-      - name: source
-        dtype: string
-      - name: domain
-        dtype: string
-      - name: definition
-        dtype: string
-      - name: parent_mechanism
-        dtype: string
-      - name: synonym_of
-        dtype: string
-      - name: antonym_of
-        dtype: string
-    splits:
-      - name: train
-  - config_name: personality_traits
-    features:
-      - name: id
-        dtype: string
-      - name: name
-        dtype: string
-      - name: category
-        dtype: string
-      - name: core_pattern
-        dtype: string
-    splits:
-      - name: train
-  - config_name: bias_mechanisms
-    features:
-      - name: id
-        dtype: string
-      - name: name
-        dtype: string
-      - name: definition
-        dtype: string
-    splits:
-      - name: train
-  - config_name: bias_synonyms
-    features:
-      - name: id
-        dtype: string
-      - name: primary
-        dtype: string
-      - name: notes
-        dtype: string
-    splits:
-      - name: train
-  - config_name: bias_antonyms
-    features:
-      - name: id
-        dtype: string
-      - name: opposite
-        dtype: string
-      - name: flipping_mechanism
-        dtype: string
-      - name: context
-        dtype: string
-    splits:
-      - name: train
-  - config_name: nonverbal_cues
-    features:
-      - name: id
-        dtype: string
-      - name: signal
-        dtype: string
-      - name: description
-        dtype: string
-    splits:
-      - name: train
-  - config_name: intervention_levers
-    features:
-      - name: id
-        dtype: string
-      - name: description
-        dtype: string
-    splits:
-      - name: train
-  - config_name: breathing_techniques
-    features:
-      - name: id
-        dtype: string
-      - name: name
-        dtype: string
-      - name: category
-        dtype: string
-      - name: overview
-        dtype: string
-    splits:
-      - name: train
 task_categories:
   - text-classification
   - text-generation
-configs:
-  - config_name: emotions
-    data_files:
-      - split: train
-        path: emotions/train.jsonl
-  - config_name: behavioral_loops
-    data_files:
-      - split: train
-        path: behavioral_loops/train.jsonl
-  - config_name: cognitive_biases
-    data_files:
-      - split: train
-        path: cognitive_biases/train.jsonl
-  - config_name: personality_traits
-    data_files:
-      - split: train
-        path: personality_traits/train.jsonl
-  - config_name: bias_mechanisms
-    data_files:
-      - split: train
-        path: bias_mechanisms/train.jsonl
-  - config_name: bias_synonyms
-    data_files:
-      - split: train
-        path: bias_synonyms/train.jsonl
-  - config_name: bias_antonyms
-    data_files:
-      - split: train
-        path: bias_antonyms/train.jsonl
-  - config_name: nonverbal_cues
-    data_files:
-      - split: train
-        path: nonverbal_cues/train.jsonl
-  - config_name: intervention_levers
-    data_files:
-      - split: train
-        path: intervention_levers/train.jsonl
-  - config_name: breathing_techniques
-    data_files:
-      - split: train
-        path: breathing_techniques/train.jsonl
 ---
 
-# Behavioral Taxonomy
-
-> A comprehensive, structured taxonomy for **technical mindfulness** — **239 emotions**, **1,140 behavioral loops**, **117 cognitive biases**, **29 personality traits**, **17 bias mechanisms**, **16 breathing techniques**, and more — for affective computing, NLP, and behavioral science research.
+# Behavioral Taxonomy Collection
 
-## Dataset Summary
+> A collection of **1619 entries** across **7 datasets** for technical mindfulness, affective computing, and behavioral science research.
 
-This dataset provides the foundational behavioral science and mindfulness data structures used by [AFFECTIVELY](https://affectively.ai). It categorizes human behavior, cognition, and self-regulation into structured, machine-readable formats suitable for training and evaluating AI systems that work with human emotions and behavior.
+This is the umbrella collection linking to all individual AFFECTIVELY datasets. Each dataset is independently loadable.
 
-### Core Subsets
+## Datasets
 
-| Subset | Records | Description |
-|--------|---------|-------------|
-| `emotions` | 239 | Three-level emotion hierarchy (primary, secondary, tertiary) with Ekman mappings, valence/arousal, coping tips, physiological effects |
-| `behavioral_loops` | 1,140 | Structured behavioral patterns with given/when/then/result logic, taxonomy classification, veracity scores, and intervention strategies |
-| `cognitive_biases` | 123 | Unified cognitive bias entries from 5 production sources — definitions, mechanisms, synonyms, antonyms, and domain classifications |
-| `personality_traits` | 29 | Personality trait archetypes with core patterns, observable behaviors, and mitigation strategies |
-
-### Supplementary Subsets
-
-| Subset | Records | Description |
-|--------|---------|-------------|
-| `bias_mechanisms` | 17 | Cognitive mechanisms (heuristics) that generate derivative biases |
-| `bias_synonyms` | 23 | Synonym/alias groups mapping alternative names to primary biases |
-| `bias_antonyms` | 16 | Antonym pairs with flipping mechanisms (e.g., Optimism Bias <-> Pessimism Bias) |
-| `nonverbal_cues` | 9 | Nonverbal communication patterns and contextual alerts |
-| `intervention_levers` | 6 | Intervention lever types for behavioral change |
-| `breathing_techniques` | 16 | Evidence-based breathing techniques with contraindications, benefits, and session guidance |
+| Dataset | Records |
+|---------|---------|
+| [emotions-taxonomy](https://huggingface.co/datasets/buley/emotions-taxonomy) | 239 |
+| [behavioral-loops](https://huggingface.co/datasets/buley/behavioral-loops) | 1140 |
+| [cognitive-biases](https://huggingface.co/datasets/buley/cognitive-biases) | 180 |
+| [personality-traits](https://huggingface.co/datasets/buley/personality-traits) | 29 |
+| [breathing-techniques](https://huggingface.co/datasets/buley/breathing-techniques) | 16 |
+| [nonverbal-cues](https://huggingface.co/datasets/buley/nonverbal-cues) | 9 |
+| [intervention-levers](https://huggingface.co/datasets/buley/intervention-levers) | 6 |
 
 ## Quick Start
 
 ```python
 from datasets import load_dataset
 
-# Load core subsets
-emotions = load_dataset("buley/behavioral-taxonomy", "emotions")
-loops = load_dataset("buley/behavioral-taxonomy", "behavioral_loops")
-biases = load_dataset("buley/behavioral-taxonomy", "cognitive_biases")
-traits = load_dataset("buley/behavioral-taxonomy", "personality_traits")
-
-# Load supplementary subsets
-mechanisms = load_dataset("buley/behavioral-taxonomy", "bias_mechanisms")
-breathing = load_dataset("buley/behavioral-taxonomy", "breathing_techniques")
+# Load any individual dataset
+emotions = load_dataset("buley/emotions-taxonomy")
+loops = load_dataset("buley/behavioral-loops")
+biases = load_dataset("buley/cognitive-biases", "biases")
+traits = load_dataset("buley/personality-traits")
+breathing = load_dataset("buley/breathing-techniques")
 ```
 
-## Subset Details
-
-### Emotions (239 entries)
-
-Three-level hierarchy based on established emotion research:
-
-- **7 primary emotions** — disgust, joy, sadness, anger, fear, surprise, love
-- **64 secondary emotions** — e.g., bitter, grateful, anxious, amused
-- **168 tertiary emotions** — e.g., jaded, disillusioned, resentful, euphoric
-
-Each emotion includes:
-- **Valence** (Positive/Negative/Neutral/Mixed) and **arousal** (Very Low to Very High)
-- **Ekman category** mapping to basic emotions
-- **Description** and real-world **example**
-- **Coping tips**: reflection, de-escalation, self-judgment, normalization
-- **Physiological effects** (body sensations)
-- **Related emotions** and **associated triggers**
-
-### Behavioral Loops (1,140 entries across 279 categories)
-
-Structured behavioral patterns following a given/when/then/result logic:
-
-| Field | Description |
-|-------|-------------|
-| `given` | Initial condition or context |
-| `when` | Trigger event |
-| `then` | Resulting behavior |
-| `result` | Long-term outcome |
-| `origin` | GENETIC, BEHAVIORAL, NARRATIVE, DIGITAL, ENVIRONMENTAL |
-| `modality` | VISUAL_STATIC, VISUAL_DYNAMIC, AUDITORY, HAPTIC, OLFACTORY, META, PROXEMIC |
-| `mutability` | IMMUTABLE, STUBBORN, FLUID, VOLATILE |
-| `valences` | ATTRACTION, REPULSION, DOMINANCE, SUBMISSION, TRUST, DECEPTION, DISRUPTION |
-
-Each loop also includes:
-- **Veracity scores** (0-1): objective grounding, social consensus, recursive amplification, friction index
-- **Intervention strategies**: interdict, minimize, recognize, leverage (with difficulty 1-10)
-- **Operator**: named psychological mechanism and explanation
-
-### Cognitive Biases (123 unified entries)
-
-Built from **5 production data sources** — core definitions, mechanism derivatives, synonym aliases, antonym pairs, and domain classifications. Each bias is tagged with its `source` field indicating provenance:
-
-| Source | Count | Description |
-|--------|-------|-------------|
-| `definition` | 16 | Full definitions with domains, System 1/2, observable markers, examples |
-| `mechanism_derivative` | ~70 | Biases derived from 17 cognitive mechanisms (heuristics) |
-| `synonym_alias` | ~20 | Alternative names linked to primary biases |
-| `antonym` | ~10 | Bias poles with flipping mechanisms |
-
-Based on the 4-domain functional classification:
-
-| Domain | Description |
-|--------|-------------|
-| TOO_MUCH_INFO | Information filtering and overload biases |
-| NOT_ENOUGH_MEANING | Pattern-finding and meaning-making biases |
-| NEED_TO_ACT_FAST | Decision-making shortcuts |
-| WHAT_TO_REMEMBER | Memory formation and recall biases |
-
-### Personality Traits (29 entries)
-
-Archetypal personality patterns with categories including:
-- DEFENSIVE_MASKING (The Tough Guy, The Saint, Passive-Aggressive Charmer)
-- VULNERABILITY_DEFENSIVE (The Victim, The People Pleaser)
-- CONTROL_ORIENTED (The Control Freak, Domineering Behavior)
-- ACHIEVEMENT_PERFORMANCE (The Achiever, The Perfectionist)
-
-### Breathing Techniques (16 entries)
-
-Evidence-based breathing practices for emotional regulation:
-
-- **Categories**: Foundational/Calming, Energizing, Advanced, Specialized
-- Each includes: overview, contraindications, recommended session duration, difficulty level, primary benefits
-- Designed for integration into mindfulness applications and therapeutic tools
-
-### Bias Mechanisms (17 entries)
-
-The cognitive heuristics that generate derivative biases — e.g., Availability Heuristic, Prospect Theory, Attribution Theory, Cognitive Dissonance. Each mechanism maps to its derivative biases.
-
-### Bias Synonyms (23 entries) and Antonyms (16 entries)
-
-Synonym groups map alternative names to primary biases (e.g., Gambler's Fallacy = Monte Carlo Fallacy). Antonym pairs include flipping mechanisms explaining when one bias pole activates over another (e.g., Optimism Bias flips to Pessimism Bias via depression/anxiety).
-
-## Use Cases
-
-- **Emotion AI / Affective Computing** — train classifiers, build emotion wheels, design empathetic chatbots
-- **NLP & Text Classification** — emotion labels, bias detection, personality typing
-- **Mental Health & Mindfulness** — coping strategies, breathing exercises, self-awareness tools
-- **Behavioral Analysis** — loop detection, intervention planning, pattern recognition
-- **Cognitive Bias Research** — unified bias taxonomy with mechanism provenance and synonym resolution
-- **Game Design & Narrative** — character personality systems, emotional arcs
-- **Human-Computer Interaction** — adaptive interfaces, sentiment-aware UX
-
 ## Also Available as npm Package
 
 ```bash
 npm install @affectively/behavioral-taxonomy
 ```
 
-```typescript
-import { getBehavioralLoops, getEmotions, getBiases, getTraits } from '@affectively/behavioral-taxonomy';
-```
-
 ## Citation
 
 ```bibtex
-@dataset{affectively_behavioral_taxonomy_2026,
+@dataset{buley_behavioral_taxonomy_2026,
   author = {Taylor Buley},
-  title = {Behavioral Taxonomy: Emotions, Loops, Biases, Traits \& Mindfulness Techniques},
+  title = {Behavioral Taxonomy Collection},
   year = {2026},
   publisher = {HuggingFace},
   url = {https://huggingface.co/datasets/buley/behavioral-taxonomy},
@@ -358,12 +78,8 @@ import { getBehavioralLoops, getEmotions, getBiases, getTraits } from '@affectiv
 
 [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)
 
-You are free to share and adapt this dataset for any purpose, even commercially, as long as you give appropriate credit.
-
 ## About
 
 Published by [AFFECTIVELY](https://huggingface.co/affectively-ai) · Managed by [@buley](https://huggingface.co/buley)
 
-AFFECTIVELY transforms high-entropy emotional experiences into low-entropy, actionable insights through technical mindfulness.
-
-- [npm package](https://www.npmjs.com/package/@affectively/behavioral-taxonomy) · [GitHub](https://github.com/affectively-ai/behavioral-taxonomy) · [All models](https://huggingface.co/affectively-ai) · [Edgework.ai](https://edgework.ai)
+- [All datasets](https://huggingface.co/buley) · [All models](https://huggingface.co/affectively-ai) · [GitHub](https://github.com/affectively-ai) · [Edgework.ai](https://edgework.ai)