Observational Data Quality
Observational Data Quality is a scholarly construct that denotes the rigor, accuracy, and trustworthiness of data acquired through systematic observation, distinguished by its focus on the validity, reliability, and completeness of recorded observational phenomena within empirical research contexts.
547
Publications
33.8K
Citations
2.1K
Authors
985
Institutions
Publications per year
2017–2026
155
Parents
547
Why we need observational studies to evaluate the effectiveness of health care
BMJ · 1996 · 1.6K citations
Pattern and variation of C:N:P ratios in China’s soils: a synthesis of observational data
Hanqin Tian, Guangsheng Chen, Chi Zhang et al. · Biogeochemistry · 2009 · 841 citations
VOSA: virtual observatory SED analyzer
A. Bayo, C. Rodrigo, D. Barrado et al. · Astronomy and Astrophysics · 2008 · 588 citations · Full text
Natural Sciences, Astronomy, Physics +11
1–5 of 547
2.1K
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985

Chinese Academy of Sciences
Beijing, China
13 h-index
55 publications
1.6K citations

Centre National de la Recherche Scientifique
Paris, France
12 h-index
41 publications
1K citations
Harvard University
Cambridge, United States
11 h-index
23 publications
1.2K citations
University of Oxford
Oxford, United Kingdom
10 h-index
20 publications
1.2K citations
University of California, Los Angeles
Los Angeles, United States
9 h-index
12 publications
727 citations
Columbia University
New York, United States
8 h-index
14 publications
607 citations
ETH Zurich
Zurich, Switzerland
8 h-index
18 publications
920 citations
University of California, Berkeley
Berkeley, United States
8 h-index
8 publications
1.2K citations
1–8 of 985
44 publications · 3.5K citations
26
h-index
24 publications · 1.7K citations
17
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ApJ · 20 publications · 1.6K citations
16
h-index
JGR · 15 publications · 669 citations
13
h-index
AJ · 10 publications · 957 citations
10
h-index
1–5