Data Completeness
Data Completeness is a data quality dimension that refers to the extent to which all required data elements are present within a dataset, distinguishing itself by measuring the absence of missing values in relation to a defined set of expected attributes or records.
348
Publications
24.9K
Citations
1.6K
Authors
822
Institutions
Publications per year
2017–2026
182
348
Rough set approach to incomplete information systems
Marzena Kryszkiewicz · Information Sciences · 1998 · 1.3K citations
Alexei A. Vaguine, Jean Richelle, Shoshana J. Wodak · Acta Crystallographica Section D Biological Crystallography · 1999 · 902 citations
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University of Washington
Seattle, United States
10 h-index
24 publications
752 citations

Lund University
Lund, Sweden
9 h-index
15 publications
481 citations
Harvard University
Cambridge, United States
9 h-index
36 publications
7.2K citations

Johns Hopkins University
Baltimore, United States
7 h-index
22 publications
367 citations
Heidelberg University
Heidelberg, Germany
7 h-index
11 publications
497 citations

UNSW Sydney
Sydney, Australia
6 h-index
9 publications
247 citations

Centers for Disease Control and Prevention
Atlanta, United States
6 h-index
31 publications
731 citations

Uppsala University
Uppsala, Sweden
6 h-index
14 publications
307 citations
1–8 of 822
Repository · 9 publications · 2.1K citations
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JAMIA · 6 publications · 256 citations
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TKDE · 5 publications · 263 citations
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6 publications · 362 citations
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3 publications · 96 citations
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