📅 2025-08-18 — Session: Developed Publishing Strategy and Data Processing Plans
🕒 19:05–20:10
🏷️ Labels: Publishing, Data Processing, Automation, Python, Markdown
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop a comprehensive publishing strategy for Matías Automation Lab and outline data processing plans for publishing automation.
Key Activities
- Publishing Strategy: A structured vision was outlined, categorizing content into series like Handbooks, Playbooks, and Pocket Cookbooks, with specific content clusters and formats.
- Batch Annotation Plan: A plan was devised for transforming data processing clusters into actionable products, detailing deliverables and associated risks.
- Code Cell Front-Matter Stripping: Implemented a Python solution to clean Jupyter notebook cells by removing unnecessary front-matter metadata.
- Filtering Legacy Nodes: Developed a method to filter out ‘legacy’ nodes during markdown generation, ensuring clean output.
- Navigation Query: Reflected on Cluster 58’s navigation, seeking insights into its markdown file contents.
- Project Clusters Overview: Planned deliverables and next steps for project clusters related to poverty datasets, harmonization, and database design.
Achievements
- Established a clear publishing framework and data processing plans.
- Developed code solutions for cleaning and filtering in markdown processing.
Pending Tasks
- Further exploration of Cluster 58’s navigation and markdown content.
- Finalization of project deliverables for poverty datasets and harmonization.