Demo Data from SIGIR 2026 / reviewers in the wild / expert
Luis Silva
dblp:174/7852
· 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
Human-computer interaction and ubiquitous computing · 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% | |
| Human-computer interaction and pervasive computing
1 paper |
Usability and user experience research · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Empirical software engineering · 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 › visualization evaluation
information visualization evaluation |
0.2 | 1 | 2016 | Evaluating Information Visualization via the Interplay of Heuristic Evaluation and Question-Based Scoring · CHI 2016 |
Usability and user experience research › usability inspection
heuristic evaluation |
0.1 | 1 | 2016 | Evaluating Information Visualization via the Interplay of Heuristic Evaluation and Question-Based Scoring · CHI 2016 |
Usability and user experience research › evaluation methodology
visualization evaluation |
0.1 | 1 | 2016 | Evaluating Information Visualization via the Interplay of Heuristic Evaluation and Question-Based Scoring · CHI 2016 |
Methods — techniques the papers use, named apart from their topics
question-based scoring · 0.8heuristic evaluation · 0.8controlled study · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Evaluating Information Visualization via the Interplay of Heuristic Evaluation and Question-Based ScoringabstractIn an instructional setting it can be difficult to accurately assess the quality of information visualizations of several variables. Instead of a standard design critique, an alternative is to ask potential readers of the chart to answer questions about it. A controlled study with 47 participants shows a good correlation between aggregated novice heuristic evaluation scores and results of answering questions about the data, suggesting that the two forms of assessment can be complementary. Using both metrics in parallel can yield further benefits; discrepancies between them may reveal incorrect application of heuristics or other issues. Marti A. Hearst, Paul Laskowski, Luis Silva |
CHI | 3 |