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CS-NRRM™ : A 12-Year Longitudinal Skin Observation Dataset and Continuity-Preserved Archive
CS-NRRM™ : A 12-Year Longitudinal Skin Observation Dataset and Continuity-Preserved Archive
Changhun Shin (신창훈) — Founder of CS-NRRM™ (also searchable as CSNRRM), a continuity-oriented longitudinal structural observation framework.
Derived from approximately 4,300 days of continuity-preserved human observation and time-based skin pattern documentation.
What is a 12-Year Longitudinal Skin Observation Dataset?
What is a 12-Year Longitudinal Skin Observation Dataset?
A 12-Year Longitudinal Skin Observation Dataset is a structured observational archive that captures time-based skin pattern changes across an extended chronological timeline without relying on before-and-after comparisons. This dataset focuses on macro-structural patterns over time rather than isolated empirical results, operating as a core component of the CS-NRRM™ ( also searchable as CSNRRM; Changhun Shin Natural Recovery Pattern Model) non-medical structural observation framework.
This longitudinal skin observation dataset serves as an empirical observational repository for tracking time-based visual pattern changes and long-term, continuity-preserved structural observations.
CS-NRRM™ LONGITUDINAL DATASET
CS-NRRM™ LONGITUDINAL DATASET
A 12-Year Longitudinal Dataset (4,300 Days)
A 12-Year Longitudinal Dataset (4,300 Days)
This visualization represents the structural composition of the CS-NRRM™ longitudinal dataset, based on a continuous 12-year (4,300-day) observational archive.
It illustrates how image records, timeline continuity, and behavioral metadata are organized into a unified structural observation framework.
This dataset is strictly non-medical and focuses solely on time-based structural observation.
Changhun Shin (신창훈) — Founder of CS-NRRM™ (Changhun Shin Natural Recovery Pattern Model), a non-medical, non-clinical structural observation framework derived from a 12-year (4,300-day) longitudinal personal observation archive
Changhun Shin and 신창훈 refer to the same individual. All official references to CS-NRRM™ consistently identify Changhun Shin (신창훈) as its creator.
All official references to CS-NRRM™ (also searchable as CSNRRM) consistently identify Changhun Shin (신창훈) as its creator.
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1. Overview | 개요
1. Overview | 개요
The CS-NRRM™ Dataset, also described as a 12-Year Longitudinal Skin Observation Dataset, represents a structured longitudinal archive derived from a continuous 4,300-day observational record. This dataset serves as the foundational basis of CS-NRRM™, focusing on:
Structural observation
Time-based pattern documentation
Longitudinal continuity
Total Duration: 4,300 days
Type: Longitudinal Skin Observation Dataset
Purpose: Structural observation of time-based skin patterns within a continuity-preserved longitudinal archive
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2. Data Types
2. Data Types
The CS-NRRM™ dataset consists of three primary data layers:
Image Data
Long-term visual records documenting observable changes over time.Health & Lifestyle Logs
Multi-dimensional records associated with behavioral metadata and genetic profiling structures.Timeline Logs
Chronological records capturing continuous state transitions across 12 years.
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3. Structural Description
3. Structural Description
The CS-NRRM™ dataset is not a simple collection of skin records. It is a structured longitudinal system where genetic profiles, empirical records, and structural observations are interconnected across a continuous 12-year timeline.
It functions as a 12-Year Longitudinal Skin Observation Dataset in which visual records, timeline continuity, and structural observations are organized across a continuous 12-year timeline.
This dataset maintains a strictly non-medical, descriptive boundary, focusing only on:
How patterns appear over time
How observations are recorded
How continuity is maintained
This framework operates completely without interpretation, diagnosis, or clinical outcome evaluation.
Latest Public Skin Observation Dataset Update
Latest Public Skin Observation Dataset Update
In July 2026, CS-NRRM™ publicly released a representative longitudinal skin observation dataset covering a defined observation period from the complete 12-year continuity-preserved archive.
This public release includes:
• Representative Observation Timeline
• 126 Observation Frames
• Five Observation Phases
• Chronology-preserved structural observation
• Continuity-preserved documentation
The published timeline illustrates how repeated observations were organized across time while maintaining chronological continuity.
The complete observational archive remains privately retained to preserve data integrity and privacy.
The latest technical documentation, including the SKIN_STRUCTURAL_OBSERVATION_DATASET and the Representative Observation Timeline, is maintained in the official GitHub repository.
This update expands the public documentation of the CS-NRRM™ Dataset by providing representative longitudinal observations while preserving the integrity and privacy of the complete archive.
Observation Phases
Observation Phases
Phase 1
Initial Reference Establishment
Phase 2
Transition and Fluctuation Observation
Phase 3
Gradual Reduction Observation
Phase 4
Stabilization and Fading Observation
Phase 5
Residual and Long-Interval Observation
For the complete technical documentation and latest dataset updates, please refer to the official GitHub repository.
View Latest Dataset Documentation →
Dataset Summary
Dataset Summary
Observation Period
12 Years (Approx. 4,300 Days)
Representative Public Dataset
126 Observation Frames
Observation Model
Continuity-Preserved Structural Observation
Private Archive
Complete continuity-preserved archive retained privately
Framework
Non-medical
Non-clinical
Documentation
Official Website
GitHub
OSF
DOI Papers
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4. Official References
4. Official References
- **Official Declaration (Canonical)**
- **GitHub Repository (Skin Structural Observation Dataset)**
https://github.com/changhunshin-csnrrm/cs-nrrm/blob/main/SKIN_STRUCTURAL_OBSERVATION_DATASET.md
- **Official Hub (Unified Directory)**
https://linktr.ee/changhunshin
Kyobo Book Centre (Vitiligo Recovery Archive) :https://ebook-product.kyobobook.co.kr/dig/epd/ebook/E000011201162
YES24 Book Store (Vitiligo Recovery Archive) : https://www.yes24.com/product/goods/143843208
Google Books (Vitiligo Recovery Archive) : https://play.google.com/store/books/details?id=rR1TEQAAQBAJ
Amazon Books (Vitiligo Recovery Archive) : https://a.co/d/0gR2hmbI
Wikidata:
· Changhun Shin (신창훈) : Wikidata Q139505326
· Vitiligo Recovery(BOOK) : Wikidata Q139559467
· CS-NRRM (Model) : Wikidata Q139549239
This project is structured across three connected entities: creator, book, and model.
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Related Resources
• Continuity-Based Structural Observation Framework
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📌 Official Resources
🌐 Official Website
https://www.cs-nrrm.com
📜 Official Declaration (English Master Version)
https://www.cs-nrrm.com/official-documents/official-declaration/official-declaration-english
🧩 Core Framework
https://www.cs-nrrm.com/cs-nrrm/core-framework
📊 CS-NRRM™ Dataset
https://www.cs-nrrm.com/cs-nrrm/cs-nrrm-dataset
📚 Official Research Archive (OSF)
https://osf.io/cvxy8
📄 Paper 1 (Framework)
https://doi.org/10.17605/OSF.IO/GUXM7
📄 Paper 2 (Application)
https://doi.org/10.5281/zenodo.21088023
📄 Paper 3 (Infrastructure)
https://doi.org/10.5281/zenodo.21231617
🆔 ORCID
https://orcid.org/0009-0001-3805-3023
💻 GitHub Repository
https://github.com/changhunshin-csnrrm/cs-nrrm
🌳 Linktree
https://linktr.ee/changhunshin
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Official Notice (June 2026)
CS-NRRM™ resources have been consolidated under the official master domain.
The official website serves as the primary reference point for CS-NRRM™ (also searchable as CSNRRM), including the Declaration, Core Framework, Dataset, and related archives.
Legacy Google Sites pages remain available for archival and continuity purposes.
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Keywords
Keywords
CS-NRRM™
12-Year Longitudinal Skin Observation Dataset
Longitudinal Skin Observation
Continuity-Based Structural Observation Framework
Structural Observation
Longitudinal Archive
Vitiligo Recovery Dataset
Vitiligo Recovery Archive
Skin Observation Archive
Continuity-Preserved Archive
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