Methodologies

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  • Terminology/taxonomy
  • Data quality harmonization
  • Best practices in different communities
  • Level 2 Quality flags (and what do they tell about the product quality)
  • Level 3 "Quality" (what’s that?)
  • Propagation of L2 uncertainty to L3
  • Effects of missing data on aggregates
  • Data quality ontology (The Semantic Web Cluster is already working on logistics of the Data Quality Ontology breakout session)
  • Presenting data quality to users

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