Missing Data Queries
Missing Data Queries is a query management framework that systematically identifies, characterizes, and addresses incomplete or absent data elements within a dataset by formalizing the conditions under which data gaps affect analytical validity and prescribing actions for their resolution.
43
Publications
1.4K
Citations
114
Authors
67
Institutions
Publications per year
2017–2026
15
Parents
43
Data Voids: Where Missing Data Can Easily Be Exploited
danah boyd, Michael Golebiewski · 2018 · 107 citations
Skyline queries in crowd-enabled databases
Christoph Lofi, Kinda El Maarry, Wolf‐Tilo Balke · 2013 · 66 citations
1–5 of 43
114
4
h-index
4
h-index
3
h-index
2
h-index
2
h-index
1–5 of 114
67

University of Edinburgh
Edinburgh, United Kingdom
5 h-index
6 publications
171 citations

International Islamic University Malaysia
Kuala Lumpur, Malaysia
2 h-index
5 publications
65 citations
Technische Universität Braunschweig
Braunschweig, Germany
2 h-index
5 publications
273 citations
University of Antwerp
Antwerp, Belgium
2 h-index
2 publications
62 citations

Zhejiang University
Hangzhou, China
2 h-index
8 publications
364 citations
Université Paris-Sud
Orsay, France
2 h-index
3 publications
42 citations

Heriot-Watt University
Edinburgh, United Kingdom
2 h-index
2 publications
40 citations
University of Stuttgart
Stuttgart, Germany
2 h-index
3 publications
39 citations
1–8 of 67
PVLDB · 6 publications · 231 citations
6
h-index
TKDE · 5 publications · 169 citations
5
h-index
2 publications · 27 citations
2
h-index
1 publications · 13 citations
1
h-index
1 publications · 13 citations
1
h-index
1–5