Difference between revisions of "FAIR Dataset Quality Information"
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<big>'''Multi-dimensions of Data and Information Quality:''' </big><br> | <big>'''Multi-dimensions of Data and Information Quality:''' </big><br> | ||
* Quality Attributes for Data Consumers [https://www.tandfonline.com/doi/abs/10.1080/07421222.1996.11518099 (Wang and Strong 1996)] <br> | * Quality Attributes for Data Consumers [https://www.tandfonline.com/doi/abs/10.1080/07421222.1996.11518099 (Wang and Strong 1996)] <br> | ||
− | * Multi-dimensions of Earth Science Data and Information Quality [http://www.dlib.org/dlib/july17/ramapriyan/07ramapriyan.html (Ramapriyan et al. 2017)] | + | * Multi-dimensions of Earth Science Data and Information Quality [http://www.dlib.org/dlib/july17/ramapriyan/07ramapriyan.html (Ramapriyan et al. 2017)] <br> |
<big>'''Existing Fitness for Purpose Assessment approaches Through the Full Life Cycle of Earth Science Datasets:''' </big><br> | <big>'''Existing Fitness for Purpose Assessment approaches Through the Full Life Cycle of Earth Science Datasets:''' </big><br> | ||
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** Perspectives of data uncertainty [https://esip.figshare.com/articles/Understanding_the_Various_Perspectives_of_Earth_Science_Observational_Data_Uncertainty/10271450 (Moroni et al. 2019)] <br> | ** Perspectives of data uncertainty [https://esip.figshare.com/articles/Understanding_the_Various_Perspectives_of_Earth_Science_Observational_Data_Uncertainty/10271450 (Moroni et al. 2019)] <br> | ||
** OGC UncertML (Williams et al. 2009) <br> | ** OGC UncertML (Williams et al. 2009) <br> | ||
− | ** Operational Readiness Levels For Disaster Operations ESIP Disasters Cluster 2018) <br> | + | ** Operational Readiness Levels For Disaster Operations (ESIP Disasters Cluster 2018) <br> |
* Product quality: <br> | * Product quality: <br> |
Revision as of 13:37, June 4, 2020
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)
- CORE-CLIMAX production system maturity matrix (EUMETSAT 2013)
- 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)
- NASA Technical Readiness Levels for Operations (Mankins 2009)
- Product quality:
- NOAA CDR product maturity matrix (Bates and Privette 2012)
- NOAA CDR product maturity matrix (Bates and Privette 2012)
- Stewardship quality:
- NCEI/CICS-NC scientific data stewardship maturity matrix Peng et al. 2015);(Peng et al 2019b)
- CEOS WGISS data management and stewardship maturity matrix (WGISS DSIG 2017)
- WMO stewardship maturity matrix for climate data (SMM-CD Working Group 2019)
- GEOSS Data Management Principles and Data Sharing Principles (GEO DMP TF 2015); (GEO DSWG 2014)
- NCEI/CICS-NC scientific data stewardship maturity matrix Peng et al. 2015);(Peng et al 2019b)
- Service quality:
- NSIDC level of services (Duerr et al. 2009)
- NCEI tiered scientific data stewardship services (Peng et al. 2016)
- GCOS ECV Data and Information Access Matrix (website)
- Global Ocean Observing System (GOOS) framework (website)
- NCEI/ESIP-DSC data use and services maturity matrix (Serv-MM Working Group 2018)
- Data Impact (Downs 2019)
- NSIDC level of services (Duerr et al. 2009)
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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