ProtoGraph: A Non-Expert Toolkit for Creating Animated Graphs
Bibliographic record
Abstract
Creating intuitive and aesthetically pleasing visualizations and animations of small-to-moderate-sized graphs in the form of node-link diagrams is a common task across many fields, particularly in pedagogical settings. However, creating a graph visualization either requires users to manually construct a graph by hand or programming skills. We present ProtoGraph, an English-like programming language for non-expert users to rapidly specify and animate node-link graph visualizations. The language supports iterative prototyping, thereby allowing non-experts users to intuitively refine their graphs, and to easily create animated graphs. The key features of ProtoGraph include a web-based live coding interface, previews for the different states in an animated graph, integrated user documentation, and an active-learning style tutorial. We have integrated the ProtoGraph language into an open-source JavaScript graph visualization library for rendering and a graphical web interface for rapid prototyping. In a user study, we show that participants with varying coding experiences were able to quickly learn the ProtoGraph language and create real-world pedagogical visualizations, showing that ProtoGraph is easy to learn, efficient to use, and extensible.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".