Expanding the Scope: Interaction Design Perspectives for Visual Analytics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, we explore the current state of interaction design in visual analytics. Current visual analytics design is heavily focused on interface issues like scalability and tool functionality; this focus is necessary, but it should not be exclusive. Further, most consideration of human cognition is done after tool development in the form of limited evaluation. We argue that, by definition, visual analytics is the science of analytical reasoning facilitated by visual interfaces, and as such, should consider complex human cognition in visual analytics design before and after tool development. We discuss two extant approaches to interaction design (Activity Theory and Participatory Design) and discuss how they might be applied, as well as the potential benefits to these approaches. We also introduce a design tool adapted for visual analytics, and provide an example of visual analytics interaction design in action. Future implications of this work are also discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it