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CGIAR/knowledge-value-lab

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App README

Knowledge Value Lab (KVL)

Measuring the Marginal Value of Knowledge Assets for AI Systems

KVL quantifies how much a knowledge document contributes to AI systems across five dimensions, producing a single weighted Knowledge Value Score (KVS).

How to Use

  1. 1.Upload a Markdown (.md) document
  2. 2.Click Evaluate Knowledge Value
  3. 3.Review the scored report and download it

Dimensions

DimensionWeightWhat it measures
Knowledge Novelty30%How much of the document is unknown to the base model
Retrieval Utility20%How well the document surfaces in RAG search
Generation Utility25%How much RAG answers improve over baseline
Attribution & Grounding15%How faithfully answers are grounded in the document
Demand Utility10%How frequently this knowledge is needed by users

Score Classifications

ScoreClassification
81–100Transformational Value
61–80High Value
41–60Moderate Value
21–40Incremental Value
0–20Minimal Value

Important Note

Knowledge Novelty and Generation Utility scores are model-relative — they measure value against specific AI models and will change when models are updated. Always report scores alongside the model names and evaluation date shown in each report.