FAIR Dataset Quality Information

Document

This is the document for community guidelines of consistently curating and representing dataset quality information, in line with the FAIR principles.

Overview

This document provides resources for developing community guidelines for consistently curating and representing dataset quality information and captures the outcomes. The guidelines aims to help curate dataset quality information that is findable and accessible, machine- and human-readable, interoperable, and reusable.

Resources

Multi-dimensions of Data and Information Quality:

• Quality Attributes for Data Consumers (Wang and Strong 1996)
  
• Multi-dimensions of Earth Science Data and Information Quality (Ramapriyan et al. 2017)
  
  

Existing Fitness for Purpose Assessment approaches Through the Full Life Cycle of Earth Science Datasets:

• Overview of Maturity Models (Peng 2018; Peng et al. 2019a: Recording)
  
• Measurement system: (Thorne et al 2015)
  
• Production system:
  
  • CORE-CLIMAX production system maturity matrix (EUMETSAT 2013)
    
  • QA4ECV (Nightingale et al. 2018)
    
• Scientific quality:
  
  • NASA Technical Readiness Levels for Operations (Mankins 2009)
    
  • NOAA STAR data product algorithm maturity matrix (Zhou, Divakarla & Liu 2016)
    
  • Perspectives of data uncertainty (Moroni et al. 2019)
    
  • OGC UncertML (Williams et al. 2009)
    
  • Operational Readiness Levels For Disaster Operations ESIP Disasters Cluster 2018)
    
• Product quality:
  
• Stewardship quality:
  
• Service quality:
  
  

Dataset-level metadata quality:

• Completeness: NCEI Collection-Level Metadata Rubric Tool
  
• FAIR metadata checklist – NCEAS MetaDIG
  
• Metadata checklist of LTER network data management system
  
  

Portfolio Management and Repository Certifications

• NGDA Data Lifecycle Maturity Model (LMM)
  
• WDS-DSA-RDA core trustworthy data repository requirements
  
• USGS Trusted Data Repository Checklist
  
  

FAIR Data Principles

• FAIR Data Principles
  
• RDA FAIR Data Maturity Indicators
  
  

Organizational Challenges & Approaches

• NASA’s ESDSWG Data Quality Working Group Recommendations
  
• Gaps in Essential Climate Variables Assessment
  
• FAIR and Data Management for a Multidisciplinary Research Center
  
  

Data Quality Management Framework

• High Quality Global Data Management Framework for Climate Data (HQ-GDMFC)
  
• Conceptual Enterprise Framework for Managing Scientific Data Stewardship
  
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