Demo Data from EDBT 2026 / reviewers in the wild / expert
Thomas P. Santoro
dblp:67/6294
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2004
—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.
| Human-computer interaction and pervasive computing
1 paper |
Usability and user experience research · 87% Collaborative and social computing · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Usability and user experience research
cognitive modeling |
0.0 | 1 | 2004 | Computational GOMS modeling of a complex team task: lessons learned · CHI 2004 |
Usability and user experience research › human performance modeling
GOMS modeling |
0.0 | 1 | 2004 | Computational GOMS modeling of a complex team task: lessons learned · CHI 2004 |
Methods — techniques the papers use, named apart from their topics
computational GOMS · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | Computational GOMS modeling of a complex team task: lessons learnedabstractThis paper presents the lessons learned when a computational GOMS modeling tool was used to evaluate user interface concepts and team structure designs for a new class of military shipboard workstations. The lessons are both encouraging and cautionary: For example, computational GOMS models scaled well to a large and complex task involving teams of users. Interruptability and working memory constructs had to be added to conventional GOMS model concepts. However, two surprises emerged: First, the non-psychological aspects of the model construction were the practical bottleneck. Second, user testing data in this domain were difficult to collect and lacked definition, meaning that the model provided a better characterization of the design details than the user testing data. Included in these lessons are recommendations for future model applications and modeling methodology development. David E. Kieras, Thomas P. Santoro |
CHI | 2 |