Background Data Quality Assessment
Background Data Quality Assessment is a scholarly evaluation framework that systematically identifies, analyzes, and verifies the accuracy, completeness, consistency, and reliability of background data within a given dataset or information system to ensure its suitability for academic research and analytical applications.
23
Publications
3.8K
Citations
87
Authors
41
Institutions
Publications per year
2017–2026
3
Parents
23
1–5 of 23
87
2
h-index
Amsterdam UMC Location Vrije Universiteit Amsterdam, Netherlands
2 publications · 2.4K citations
2
h-index
2
h-index
Berufsgenossenschaft für Gesundheitsdienst und Wohlfahrtspflege, Germany
2 publications · 88 citations
2
h-index
2
h-index
1–5 of 87
41

University of Toronto
Toronto, Canada
2 h-index
2 publications
2.4K citations
Mount Sinai Hospital
Chicago, United States
2 h-index
2 publications
2.4K citations
Office of Extramural Research
Bethesda, United States
2 h-index
4 publications
4.7K citations
Berufsgenossenschaft für Gesundheitsdienst und Wohlfahrtspflege
Hamburg, Germany
2 h-index
6 publications
264 citations

Amsterdam UMC Location Vrije Universiteit Amsterdam
Amsterdam, The Netherlands
2 h-index
2 publications
2.4K citations

Toronto General Hospital
Toronto, Canada
2 h-index
2 publications
2.4K citations
University Health Network
Toronto, Canada
2 h-index
2 publications
2.4K citations
Institute for Work & Health
Toronto, Canada
2 h-index
6 publications
7.1K citations
1–8 of 41
4 publications · 2.5K citations
4
h-index
2 publications · 88 citations
2
h-index
1 publications · 11 citations
1
h-index
1 publications · 36 citations
1
h-index
1 publications · 134 citations
1
h-index
1–5