Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

The Availability Heuristic01:08

The Availability Heuristic

7.0K
A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
7.0K
The Representativeness Heuristic02:13

The Representativeness Heuristic

16.8K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
16.8K
The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

7.8K
In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
7.8K
Heuristics01:21

Heuristics

730
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
730
ATP Driven Pumps I: An Overview01:27

ATP Driven Pumps I: An Overview

9.9K
ATP-driven pumps, also known as transport ATPases, are integral membrane proteins. They have binding sites for ATP located on the membrane's cytosolic side and the ion-conducting domain in the transmembrane region. These pumps use the free energy released from ATP hydrolysis to move the solutes across cell membranes against an electrochemical gradient.
There are four main types of ATP-driven pumps - P-type, V-type, F-type, and ABC transporter. All these pumps are of varying complexities and...
9.9K
Xylem and Transpiration-driven Transport of Resources02:03

Xylem and Transpiration-driven Transport of Resources

26.8K
The xylem of vascular plants distributes water and dissolved minerals that are taken up by the roots to the rest of the plant. The cells that transport xylem sap are dead upon maturity, and the movement of xylem sap is a passive process.
26.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same authorSame journal

The Influence of Between- and Within-map Lightness Variation on Decision Making with Hazard Maps.

IEEE transactions on visualization and computer graphics·2026
Same author

Self-administered digital vaccination decision-aids in primary care: A pilot study of COVID-19 vaccination in Atlanta, GA.

Digital health·2026
Same author

Targeting dopamine D2 receptors to alter fear extinction in adolescent rats.

Behavioral neuroscience·2026
Same author

Visualizing Trust: How Chart Embellishments Influence Perceptions of Credibility.

IEEE transactions on visualization and computer graphics·2025
Same author

How Visually Literate Are Large Language Models? Reflections on Recent Advances and Future Directions.

IEEE computer graphics and applications·2025
Same author

More Like Vis, Less Like Vis: Comparing Interactions for Integrating User Preferences Into Partial Specification Recommenders.

IEEE transactions on visualization and computer graphics·2025

Related Experiment Video

Updated: Feb 5, 2026

A Data-Driven Approach to Quantifying Immune States in Sepsis
07:42

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

546

A Heuristic Approach to Value-Driven Evaluation of Visualizations.

Emily Wall, Meeshu Agnihotri, Laura Matzen

    IEEE Transactions on Visualization and Computer Graphics
    |September 7, 2018
    PubMed
    Summary

    Background color influences how people interpret colormaps. Opacity perception in colormaps can override the common dark-is-more bias, especially on dark backgrounds, impacting data visualization design.

    More Related Videos

    Using Looming Visual Stimuli to Evaluate Mouse Vision
    05:07

    Using Looming Visual Stimuli to Evaluate Mouse Vision

    Published on: June 13, 2019

    12.3K
    Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
    08:03

    Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

    Published on: December 7, 2021

    2.8K

    Related Experiment Videos

    Last Updated: Feb 5, 2026

    A Data-Driven Approach to Quantifying Immune States in Sepsis
    07:42

    A Data-Driven Approach to Quantifying Immune States in Sepsis

    Published on: February 7, 2025

    546
    Using Looming Visual Stimuli to Evaluate Mouse Vision
    05:07

    Using Looming Visual Stimuli to Evaluate Mouse Vision

    Published on: June 13, 2019

    12.3K
    Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
    08:03

    Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

    Published on: December 7, 2021

    2.8K

    Area of Science:

    • Data Visualization
    • Cognitive Psychology
    • Human-Computer Interaction

    Background:

    • Interpreting data visualizations requires mapping visual features to concepts.
    • Colormaps map color dimensions (e.g., hue, lightness) to data quantities.
    • Matching visualizations to user's inferred mappings enhances interpretation.

    Purpose of the Study:

    • Investigate how background color influences inferred color-quantity mappings in colormaps.
    • Resolve conflicting prior research on background color effects.
    • Understand factors influencing inferred mappings for effective visualization design.

    Main Methods:

    • Experimental study examining participant inferences of color-quantity relationships.
    • Manipulation of colormap opacity perception and background color.
    • Analysis of inferred mappings based on participant responses.

    Main Results:

    • Inferred color-quantity mappings are influenced by perceived colormap opacity and background color.
    • A 'dark-is-more' bias occurs when colormaps lack apparent opacity variation.
    • An 'opaque-is-more' bias emerges with increased apparent opacity, potentially overriding the 'dark-is-more' bias on dark backgrounds.

    Conclusions:

    • Colormap design should consider perceived opacity and background color to align with user inferences.
    • To ensure robust and intuitive colormaps, select designs with consistent opacity perception.
    • Encoding larger quantities with darker colors is recommended when opacity variation is minimal.