Highlights

Session 1

• Progresive data analysis (DS): adjust latency based on people's expectations. Lookup pictures later
• Motif-based dynamic network analysis - send links to Ron, linked small multiples make graph analysis tractable

Session 2

• Rebecca Faust Anteater is so cool- visualize program state over time. Specify what you care about (sort of) in advance, store program state in a DB. Kate Isaacs former PI, (now at Utah)
• Communication analysis paper... need to review more. Learned about SurVis (publish browser for BibTex). Need to analyze its techniques/would people use Datasette as compliment. Can add hover timeseries card to each faceted tag (or in DD)
• Remco Chang Keynote... a conceptual framework for describing hypothesis... what does that mean for auto vis analysis? Do we need to be stricter about what a "task" is? paper

Session 3

• Captions are what people read first... more text is better paper, 2k responses!

Session 4

• Natural language UI vis helps people edo EDA better (with Eugene Wu). Leaned on Codex model to generate structured SQL (didn't train own LLM). https://ieeevis.b-cdn.net/vis_2022/pdfs/w-nlvis-1011.pdf

Highlights

Session 1

• Learned of Schmoo Plots for chip yield boost. Detail.
• VAOS and Post Silicon Validation UIs -> worth browsing the demos/videos

Session 2

• Observability / Domain Specific (Danyel Fisher, former Sanddance)
  • "Choosing the groupby" problem - Check Eugene Wu's Scorpion paper
  • Check BubbleUp plot: combine heatmap along with distribution on hover examplars.
  • Earth mover algorithms for sorting groupbys (distance between 2 probabilities)
• Submit quality/flakiness CI vis next year
• General purpose DAG vis

Session 3

• Visguides: "Lessons Learned" over "best practices". Browse Edgemaps
• Ian's AI Explainer Design Patterns: slides. Should rewatch opener / diff Interactive Stories
  • https://xai-primer.com/tool

Session 4

• Try Distill template

Highlights

Test of Time

• Read the enterprise data analysis paper (2012)
• Try SpaceTree - hint at subtrees with glyph (2002)
• Design studies methodology: "goal = transferability not converge same solution"
• "necessity is the mother of adoption": morse-smale computation

Best paper awards

• Affective viz paper: a framework for how we think about whether viz are working
• Multiple Forecast viz: effect of color on trust + ensemble ML models + isolating effects of vis choices
• See the D3 evolution paper to learn about API design effects on wild in Stackoverflow

Keynote (Marti Hearst) - ADD MORE TEXT TO GRAPHS

• "Language should be considered co-equal with viz
• Check her Wikipedia: Flamenco project, faceted search

Industry

• 6 feet of rain graphics : how much attention does your viewer have?
• When research roadmap is long, don't let up on coming up with littler milestones, not losing connection to business
• Ethical responsibilities as consumer of OSS / publication

Highlights

• Tabular data and gramars
  • visualizations + recommendations can help w/ both graph config, data transforms, and query formula definitions (e.g verb previews)
    • HiTailor: "recipes" can fit into categories (change, distro)
  • Animated Vega Lite for presentation quality / DSLs for API design on core-viz
• Responding / Evaluation
  • Examine frameworks for how we decide whether a viz is "working" (both for aesthetics and function)
  • Think about epilepsy risk with animations/color choice
  • Progressive loading coms (multistep queries, changing the bin size by timeframe size)
• Graph Systems
  • nl4dv python package: build graphs in stages to learn VL. See tweet
  • Vega Fusion: for expensive vega lite specs
  • resampler: a visualization-aware sampling algorithm - could use in experimental form with tiny buckets for big timeseseries that need more detail over long time periods.
• Decision Support / VA / Machine Learning
  • TimberTrek, Visual Auditor, Fuzzy Spreadsheets: all ways to fit into existing workflows (notebooks, sheets)
    • TimberTrek in particular: make use of sticky panes + an attribute-based tree slicer?
    • May need to make use of funnels, service level meatdata, etc
  • FairFuse: Do we have different ranking algos to compare?
  • ML explainability: explaining rule classifiers + compare behavior in subgroups
  • "Active Search": Recommend follow-up items in "real time"?
• Hallway Track
  • Practice notebook plugin-making
    • https://arxiv.org/pdf/2205.03963.pdf / https://github.com/poloclub/nova
    • Roundtrip (Katherine Isaacs): https://github.com/hdc-arizona/roundtrip

Highlights

• Morning P1
  • 3 taxonomies post survey framework for AI <> Viz intersections (evaluation, generation, NL, copiloting)
    • 3rd paper taxonomy probably most tied to immediate future work, could be paper group idea (find top impacting papers to prioritize?)
  • Sketch of how to do DL dashboard design training (feature space + reward function based on insight function): Dashbot
• Morning P2
  • Case studies: 2500 yrs of history, what-if analysis / SHAP plots for how online sales promos work
  • Traveler: how would we use linked views on parallel traces? Link 2-layer Gantt with Topomap linked view
  • contrails: TIL alpha-shape (generalized form of Sagar's Convex hull analysis (Edelsbrunner 1992))
  • Privacy-preserving vis (motivates looking back into differential privacy + rebrushing on basics of bayesian networks)
• Afternoon P1
  • BDFW: "tutorial" / gamelike experience for engaging someone in a vis
  • Erato: DL can help with interactive storytelling / generating supporting captions + viz
  • Roslingifier, Geostorylines main demos
• Afternoon P4: Guidance/Recommendations
  • Visualize provenance: it can help someone not get lost during EDA. History or coverage.
  • Provectories, Tradeoff (wheat) vis: summmarize log in embedding or with frequency vis
  • RUM guidance: if someone is frustrated, can you nudge a "visual fix" / next step transform without getting to clippy stage?
  • Medley: make recommendations based on INTENT (implicitly by other graphs, explicit by requesting certain compare types) - similar to storytelling sesion intent requests
  • GeVitRec: DataRecon prioritize color and positional alignment using domain specific info, not just solo one off graphs. Compare to Showme, Draco, Voyager
    • An observability specific recommender may outperform what a generic Draco alg does if we pick good heuristics

...what we demonstrate here is how a design space can be used to inject domain expertise into recommendation systems. We hope that our work makes headway on this “chicken and egg” problem, motivating further work on automating the construction of a VPDS by showing the practical benefits that can be obtained from having one available.

Highlights

• Health analytics snips
  • ClinicalPath: event annotation vis (not just in margin but dedicated explorer)
  • Solidify how Bayesian networks work
  • Chartwalk: (Honorable mention paper)
    • Sparkline per tag type
    • Datasette: if there's a time column, can we show vis per time of year/etc?
  • Dashboard evaluation framework (not just original "intent" task)
  • Explainable AI (user centric) - not just some is better than no explanation -> diff explanations are task + domain specific (Honorable mention paper)
• Capstone:
  • Check the notebooks of Galileo: drawing exercises
  • What trainings (outside of CS) help you see meaningful patterns in vis? How do we encourage expatation/

Hack Ideas

• Vis for notetaking tools / personal knowledge graphs / entity annotations (timelinejs, dendron, datasette)
• ASCII art / sparkfont, ascii graph, etc - blur text <> picture
  • https://alexwlchan.net/2018/05/ascii-bar-charts/
• Site/plugin that helps make multi paper or overlays

Hack Ideas

• Implement what Survis does but for new papers
  • https://github.com/fabian-beck/survis
• Try to redo Missingno but with JS interactivity for questionable data points
  • https://github.com/ResidentMario/missingno