In recent weeks, I’ve immersed myself in understanding LogSeq’s relationship system, aiming to unlock better ways of managing and analyzing interconnected knowledge. While this research has yielded valuable insights, it’s crucial to pause and critically evaluate my approach.

Research Journey

My investigation began with a fundamental question: How can I better understand the relationships between my notes in LogSeq? This journey unfolded in several stages:

1. Exploring and categorizing different types of relations in LogSeq
2. Developing advanced query techniques to demonstrate these relationships
3. Creating a custom notation system for describing page and block relationships
4. Designing a weighting system for different relation types
5. Attempting to develop metrics for evaluating topic contributions

While each stage provided valuable insights, a critical review has revealed several areas requiring attention:

Methodological Challenges

Minor Issues:

• Academic Rigor: The research relied heavily on personal observations without a formal methodology
• Documentation Consistency: The notation system and Mermaid diagrams varied across blog posts
• Weighting System Design: The mixing of qualitative and quantitative metrics complicated result interpretation, when a simpler multiple-key ordering approach would have sufficed

Fundamental Issues:

1. Research Focus Misalignment

   • The core goal of evaluating topic contributions was overshadowed by an excessive focus on page and block relationships
   • The concept of “contribution” remained undefined, preventing proper topic evaluation
   • The relationship analysis should have supplemented, not dominated, the topic evaluation process

2. Validation Gaps

   • No systematic validation against real-world data or alternative approaches
   • Insufficient peer review or expert consultation

3. Goal Definition

   • The research objective “contributions of topics” lacked precise definition
   • Success metrics were not established at the outset
   • The scope remained too broad and ambiguous

Research Timeline

I plan to revisit this research in Q2 2025, after completing the immediate priorities outlined below. This pause will allow time to:

• Gather practical insights from the LogSeq plugin development
• Collect real-world use cases from the community
• Refine the research methodology based on user feedback

Moving Forward

While the topic contributions research remains intriguing, I’ve decided to temporarily shift focus to more immediate priorities:

1. Client-Facing Development:

   • Building and launching a demo website for potential clients
   • Gathering user feedback and requirements

2. Tool Development

   • Creating a personal productivity plugin for LogSeq
   • Focusing on practical user needs

3. Community Engagement

   • Supporting the Odoo bookclub community
   • Addressing user challenges and gathering real-world use cases

When I return to the research, I’ll approach it with:

• Clear, measurable objectives
• A robust methodology including validation mechanisms
• Regular peer review and community feedback
• Systematic documentation and consistency checks

Future Research Direction

While measuring topic contributions remains valuable, another intriguing avenue has emerged: understanding how knowledge is progressively built and refined. This research would focus on designing effective workflows for knowledge development.

A basic knowledge-building workflow might look like:

1. Capturing fleeting thoughts in daily journals (flicker notes)
2. Refining these into permanent notes on dedicated pages
3. Synthesizing and publishing as web articles

What makes this direction particularly promising is its connection to my previous research on LogSeq’s data relations. The different relation types we identified could introduce intermediate steps between initial capture and permanent storage. This opens up interesting questions:

• What viable workflows emerge from different combinations of relation types?
• How do different workflows affect the quality and usefulness of the final content?
• What criteria should we use to evaluate and compare different workflows?

This research direction offers a more concrete, practical focus while building upon our understanding of LogSeq’s relationship system.