Demo Data from SIGIR 2026 / reviewers in the wild / expert
Jocelyn Ng
dblp:170/1709
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Energy systems and smart grids · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics
design study |
0.2 | 1 | 2016 | Matches, Mismatches, and Methods: Multiple-View Workflows for Energy Portfolio Analysis · IEEE Trans. Vis. Comput. Graph. 2016 |
Visualization and visual analytics
time series visualization |
0.2 | 1 | 2016 | Matches, Mismatches, and Methods: Multiple-View Workflows for Energy Portfolio Analysis · IEEE Trans. Vis. Comput. Graph. 2016 |
Energy systems and smart grids › building energy
building energy analysis |
0.1 | 1 | 2016 | Matches, Mismatches, and Methods: Multiple-View Workflows for Energy Portfolio Analysis · IEEE Trans. Vis. Comput. Graph. 2016 |
Methods — techniques the papers use, named apart from their topics
work domain analysis · 0.5visual encoding design · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Matches, Mismatches, and Methods: Multiple-View Workflows for Energy Portfolio AnalysisabstractThe energy performance of large building portfolios is challenging to analyze and monitor, as current analysis tools are not scalable or they present derived and aggregated data at too coarse of a level. We conducted a visualization design study, beginning with a thorough work domain analysis and a characterization of data and task abstractions. We describe generalizable visual encoding design choices for time-oriented data framed in terms of matches and mismatches, as well as considerations for workflow design. Our designs address several research questions pertaining to scalability, view coordination, and the inappropriateness of line charts for derived and aggregated data due to a combination of data semantics and domain convention. We also present guidelines relating to familiarity and trust, as well as methodological considerations for visualization design studies. Our designs were adopted by our collaborators and incorporated into the design of an energy analysis software application that will be deployed to tens of thousands of energy workers in their client base. Matthew Brehmer, Jocelyn Ng, Kevin Tate, Tamara Munzner |
IEEE Trans. Vis. Comput. Graph. | 2 |