Dataview Plugin

Mis à jour le 2025-01-04Confiance : high

dataviewobsidian-pluginyaml-frontmatterdynamic-queriesmetadata-analysisautomated-tableswiki-analyticsstructured-datallm-generated-metadata

Obsidian plugin that runs queries over page frontmatter (YAML metadata) to generate dynamic tables, lists, and analytical views. Particularly valuable in llm-wiki-pattern implementations where LLMs consistently add structured metadata to wiki pages.

Core Functionality

YAML Frontmatter Queries:

Extract and analyze metadata from wiki pages
Filter pages by tags, dates, categories, confidence levels
Generate dynamic content that updates automatically
Create analytical views across the entire knowledge base

Dynamic Generation:

Tables and lists update automatically as pages change
No manual maintenance of summary content
Always reflects current state of wiki

Metadata Patterns in LLM Wikis

Standard Frontmatter:

---
title: Page Title
category: concepts|entities|projects|sources
created: YYYY-MM-DD
updated: YYYY-MM-DD
tags: [tag1, tag2, tag3]
sources: [list of contributing sources]
confidence: high|medium|low
---

Extended Metadata:

Source count tracking
Creation and update timestamps
Confidence assessments
Category classifications
Relationship mappings

Query Examples

Recent Updates:

Pages updated in last 7 days
Most frequently updated content
Recent source integrations

Quality Analysis:

Pages with low confidence ratings
Content lacking source citations
Orphan pages without inbound links

Content Overview:

Pages by category with creation dates
Tag frequency analysis
Source contribution tracking

Use Cases in Wiki Management

Dashboard Creation:

Overview of wiki health and activity
Quick access to different content types
Monitoring of maintenance needs

Quality Assurance:

Identify content needing review or updates
Find gaps in coverage or documentation
Track source diversity and quality

Analytics and Insights:

Understand knowledge accumulation patterns
Identify most valuable content areas
Track evolution of interests and focus

LLM Integration

Automated Metadata:

LLM consistently adds structured frontmatter
Tags generated based on content analysis
Confidence levels assessed during creation
Source tracking maintained automatically

Dashboard Queries:

LLM can create Dataview queries for specific analytics
Generate custom views for different purposes
Update query logic as wiki evolves

Implementation Strategy

Gradual Adoption:

Start with basic frontmatter (title, category, dates)
Add tags and sources as patterns emerge
Implement confidence ratings for quality tracking

Query Development:

Begin with simple lists and tables
Develop more complex analytical queries over time
Create reusable query templates for common needs

Benefits for Wiki Scaling

Automated Organization:

No manual maintenance of category pages
Dynamic content reflects current state
Reduces bookkeeping burden on both human and LLM

Insight Generation:

Surface patterns not visible in individual pages
Identify trends in knowledge accumulation
Support strategic decisions about focus areas

Quality Management:

Systematic identification of maintenance needs
Data-driven approach to wiki health
Objective assessment of content quality