Data Drill-down
Data Drill-Down is an interactive data exploration technique that enables hierarchical navigation from aggregated to more granular levels of data to reveal underlying details within a dataset.
21
Publications
580
Citations
60
Authors
36
Institutions
Publications per year
2017–2026
5
Parents
21
Bee-Chung Chen, Lei Chen, Yi Lin et al. · Very Large Data Bases · 2005 · 54 citations
Avoiding drill-down fallacies with <i>VisPilot</i>
Doris Jung‐Lin Lee, Himel Dev, Huizi Hu et al. · 2019 · 50 citations
M.J. Kraak · The Cartographic Journal · 2006 · 39 citations · Full text
Computing, Geography, Cartography +11
1–5 of 21
60
5
h-index
4
h-index
4
h-index
1
h-index
1
h-index
1–5 of 60
36
Stanford University
Stanford, United States
4 h-index
8 publications
204 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
7 publications
271 citations

University of Ioannina
Ioannina, Greece
1 h-index
1 publications
28 citations
Decision Sciences (United States)
Fort Walton Beach, United States
1 h-index
1 publications
12 citations

Harvard University Press
Cambridge, United States
1 h-index
1 publications
20 citations

Fermi National Accelerator Laboratory
Batavia, United States
1 h-index
1 publications
32 citations
Ludwig-Maximilians-Universität München
Munich, Germany
1 h-index
4 publications
68 citations
University of Dhaka
Dhaka, Bangladesh
1 h-index
1 publications
25 citations
1–8 of 36
PVLDB · 2 publications · 41 citations
2
h-index
TKDE · 1 publications · 31 citations
1
h-index
Conference · 1 publications · 10 citations
1
h-index
1 publications · 32 citations
1
h-index
1 publications · 39 citations
1
h-index
1–5