drp-paper

name	drp-paper
description	Create and maintain the DRP white paper project with REANA integration
version	1.0.0
license	MIT
created	2025-04-11T00:00:00.000Z
tags	["research","paper","drp","reana"]
hermes	{"domain":"research"}

DRP Paper: Digital Research Products Framework

Overview

This skill contains a reusable operational workflow. Follow the existing task-specific steps and examples in the sections below.

Verification

• Confirm required inputs and credentials are available.
• Run the smallest safe command or example before scaling up.
• Check produced files, API responses, or plots before reporting success.

Create and maintain the DRP white paper project covering the framework for reproducible science on DRP-Hub with full REANA integration.

When to Use

• User asks to create or modify the DRP paper/white paper
• User references "DRP paper," "Digital Research Products," "drp_service," or "dictation-to-repo"
• User wants to generate a comprehensive academic paper with full REANA integration and iterative improvement

Project Location

/home/hermes/digital-research-products-framework/
├── main.tex              ← monolithic paper (all sections inlined)
├── references.bib        ← BibTeX references
├── main.pdf              ← compiled output
├── figures/
│   ├── repo_structure_diagram.png    ← repository architecture (layered)
│   ├── maturity_model.png             ← maturity model staircase
│   ├── architecture_diagram.png       ← full REANA architecture
│   ├── generate_repo_diagram.py
│   ├── generate_maturity_model.py
│   └── generate_architecture_diagram.py
├── main.aux, .log, .out, .toc, .bbl, .blg

CRITICAL: Never create or use sections/ subdirectory. All content goes in monolithic main.tex. Remove stale sections/ if it exists.

Paper Structure (10 Sections)

1. Introduction — DRP paradigm, reproducibility crisis, PUNCH4NFDI context
2. Related Work — FAIR principles, REANA/Snakemake platforms, research infrastructure
3. DRP Framework and Standards — Repository structure, governance files, FAIR metadata
4. DRP Maturity Model (L0-L4) — Progressive reproducibility with REANA integration
5. DRP-Hub and Astro Card Hub Platform — Card registry, repo linker, workflow launcher
6. drp_service Workflow Orchestrator — Central workflow engine, intent recognition, auto-generation
7. Quality Assurance and Governance — Quality checklist, roles, contribution workflow
8. Practical Development Guide — Step-by-step conversion, dictation-to-repo pipeline
9. Future Outlook and Roadmap — FDO, EOSC, community growth, drp_service evolution
10. Conclusion — Summary of framework contributions

Core Concepts

drp_service — Central Workflow Orchestrator

The drp_service receives ALL user interactions from DRP-Hub and translates them into REANA workflows:

• Input channels: Terminal, DRP Card UI, AI Chatbot, Card Generator
• Workflow selection: Checks existing drp_workflows/ for matching workflow
• Workflow generation: If no match, auto-generates REANA workflow using templates
• REANA execution: Submits workflow to REANA backend automatically
• Result sync: Pushes results back to Git, triggers CI/CD, updates DRP-Hub
• Audit trail: Logs everything in provenance.yaml

Dictation-to-Repo Pipeline

Users dictate research intent → receive fully functional Git repo with REANA workflow:

1. Dictation — User describes intent (terminal, UI, or AI chatbot)
2. Intent parsing — drp_service extracts data sources, steps, outputs
3. Repository generation — Creates complete DRP structure with governance files
4. Workflow generation — Generates reana.yaml or Snakefile from templates
5. Git commit — Commits to GitHub/GitLab automatically
6. CI/CD trigger — Runs automated tests, FAIR validation, container build
7. Publication — Ready for DRP-Hub with one click

Maturity Model (L0-L4)

Each level inherits all lower-level criteria, with increasing REANA integration:

Level	Name	REANA Integration
L0	Minimal	No workflow
L1	Documented	Basic reana.yaml may exist but not executed
L2	Reproducible	Full REANA integration — runs on any backend
L3	Automated	drp_service integration — every CI/CD triggers REANA
L4	Community	Full dictation-to-repo + federated compute (REANA, S3, SSHFS, Jupyter)

Infrastructure Integration

The drp_service integrates with all PUNCH4NFDI services:

• REANA Backend — Workflow execution
• Git Repository — Version control and CI/CD
• Jupyter Notebooks — Interactive development
• S3 Storage — Large dataset access and caching
• SSHFS Mounts — Interactive file access
• Terminal Session — Command-line operations

Figure Generation

Three Core Figures

1. repo_structure_diagram.png — Layered repository architecture

   • 5 layers: Governance, FAIR Metadata, Workflows, Software & Data, Outputs & Documentation
   • Professional hex palette, color-coded layers, clear labels
   • Script: figures/generate_repo_diagram.py

2. maturity_model.png — Staircase visualization

   • 5 levels ascending L0→L4, each showing NEW criteria only
   • Professional color palette, arrows between levels
   • Script: figures/generate_maturity_model.py

3. architecture_diagram.png — Full REANA integration architecture

   • User interaction layer → DRP-Hub → drp_service → Infrastructure
   • Shows all input channels (terminal, UI, AI, generator)
   • Shows drp_service sub-components (workflow gen, executor, registry, sync)
   • Shows infrastructure (REANA, Git, Jupyter, S3, SSHFS, Terminal)
   • Script: figures/generate_architecture_diagram.py

Figure Style Guidelines

• White background: facecolor='white'
• Professional palette: Use hex colors (blues: #2C5F8A, #4A90A4; greens: #5BA06B; reds: #C8374B; oranges: #D4872C; purples: #7B68AE)
• DPI: Minimum 200
• Typography: 13-15pt titles, 7-11pt labels
• Clean: No rainbow gradients, clear legends, consistent spacing

Compilation

cd /home/hermes/digital-research-products-framework
pdflatex -interaction=nonstopmode main.tex 2>&1 | tail -10
pdflatex -interaction=nonstopmode main.tex 2>&1 | tail -10  # second pass

Output: 20 pages, ~827KB PDF.

Writing Standards

• Formal academic tone — No conversational language
• Precise claims — No unsupported assertions
• Logical flow — Topic sentences, clear transitions
• FAIR-compliant — All claims about FAIR principles accurate
• No fabricated references — Only cite what exists in references.bib
• drp_service always italicized/code-formatted as \texttt{drp\_service}

Common Pitfalls

• Sibling conflicts: Always read_file before writing to main.tex
• Section files: Never create sections/ directory — monolithic main.tex only
• Duplicate packages: Check for duplicate \usepackage{hyperref} before patching
• Figure kwargs: FancyArrowPatch uses arrowstyle= not style= or linestyle=
• Python f-strings: Use f"\u2022 {text}" for bullets, not literal •
• Cleanup: Remove stale files after changes

Maintenance

When updating the paper:

1. Read main.tex fully with read_file (no pagination)
2. Plan changes (sections, figures, references)
3. For major changes: full write_file of main.tex
4. For small changes: patch targeted replacements
5. Regenerate figures if content changes
6. Compile twice for bibliography
7. Verify page count and check .log for errors
8. Report: project path, files modified, next step