ArticleJournal of the American Medical Informatics Association : JAMIA2024
Building color palettes in your data visualization style guides.
Article in Journal of the American Medical Informatics Association : JAMIA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Beyond Google Images: Crafting impactful images for presentations or clinical use with AI.Indian journal of psychiatry · 2025Article
- Designing visual hierarchies for the communication of health data.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Advancing the science of visualization of health data for lay audiences.Journal of the American Medical Informatics Association : JAMIA · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesData visualization style guides are standards for formatting and designing representations of information, like charts, graphs, tables, and diagrams. To assist researchers communicate their visual content in better and more effective ways, this article accomplishes two tasks. First, we take a detailed look at a data visualization style guide and its components-what it is and what it should include. Second, we create a detailed template for the color section of a data visualization style guide. TARGET AUDIENCE: Creating a data visualization style guide as described here should help researchers across multiple disciplines create better and more consistent charts, graphs, and diagrams. Such style guides are useful for individuals and organizations in their efforts to be more efficient and consistent in their data communication products. SCOPE: Data visualization style guides often include explaining the what (eg, types of charts), the why (eg, reasons for using specific colors), and the how (eg, tools or templates) of creating consistent and effective visuals that can also fit within an individual's or organization's larger design system. We use a variety of tools to create, test, and implement a data visualization color palette. We provide sample color palettes and provide step-by-step instructions on how to import those palettes into six popular data visualization tools: Microsoft Excel and PowerPoint, Tableau, PowerBI, and Adobe Illustrator and InDesign.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.