Data Clarification Processes
Data Clarification Processes is a systematic method within Query Management that identifies, resolves, and documents ambiguities, inconsistencies, or gaps in data requirements through structured interactions between stakeholders to ensure precise and unambiguous data interpretations.
6
Publications
269
Citations
31
Authors
28
Institutions
Publications per year
2017–2026
3
Parents
6
Teklewoini Mariye, Degena Bahrey Tadesse, Hagos Tasew Atalay et al. · International Journal of Endocrinology · 2020 · 17 citations · Full text
1–5 of 6
31
1
h-index
1
h-index
National Institute of Environmental Health Sciences, United States
1 publications · 60 citations
1
h-index
Institute for Health Metrics and Evaluation, United States
1 publications · 17 citations
1
h-index
1
h-index
1–5 of 31
28

Centre National de la Recherche Scientifique
Paris, France
1 h-index
2 publications
32 citations
University of Wisconsin–Madison
Madison, United States
1 h-index
1 publications
60 citations

University of Cincinnati
Cincinnati, United States
1 h-index
1 publications
60 citations
National Cancer Institute
Bethesda, United States
1 h-index
1 publications
108 citations
University of Illinois Chicago
Chicago, United States
1 h-index
1 publications
60 citations
NYU Langone Health
New York, United States
1 h-index
1 publications
108 citations

University of Massachusetts Amherst
Amherst Center, United States
1 h-index
1 publications
60 citations
Suan Dusit University
Dusit, Thailand
1 h-index
1 publications
54 citations
1–8 of 28
1 publications · 14 citations
1
h-index
1 publications · 60 citations
1
h-index
1 publications · 54 citations
1
h-index
1 publications · 16 citations
1
h-index
IJE · 1 publications · 17 citations
1
h-index
1–5