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Related Concept Videos

Ethics and Bioethics01:22

Ethics and Bioethics

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Ethics is a philosophical study of moral actions. Ethics attempts to determine what is valuable for individuals and society. It examines the rational justification of moral judgments and analyzes what is morally just, fair, and right. Bioethics is a sub-discipline of applied ethics that analyzes the philosophical, social, and legal issues in life sciences and medicine. Ethical theories serve as a foundation for decision-making and represent the viewpoints from which people seek direction. They...
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Bias01:22

Bias

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Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
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Sight Distance in a Vertical Curve01:29

Sight Distance in a Vertical Curve

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Sight distance on vertical curves is critical in roadway design. It ensures drivers can see far enough ahead to identify and respond to hazards effectively. This directly impacts safety, driver comfort, and the overall efficiency of the transportation network.Vertical curves are classified into crest and sag curves based on their geometry. For crest curves, sight distance is determined by the line of sight between a driver's eye and a small object on the road's surface. Design parameters for...
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Hindsight Biases01:12

Hindsight Biases

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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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Ethical Standards II01:23

Ethical Standards II

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Ethical standards are the backbone of nursing practice, guiding nurses as they interact with patients, families, and colleagues. These standards are crucial for providing safe, empathetic care centered on the patient's needs.
Nurses are entrusted with upholding various ethical principles and standards. Nurses forge solid therapeutic relationships using trust, empathy, autonomy, confidentiality, and professional competence.
Confidentiality is crucial, embodying respect for individual privacy...
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Principle of Equivalence01:18

Principle of Equivalence

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According to Albert Einstein (1897-1955), free-falling and feeling weightless are intrinsically linked. If a person were in free-fall under gravity, for example, diving towards the Earth from an airplane, they would feel completely weightless. Similarly, a person descending in a lift may feel partially weightless. Broadly speaking, it is assumed that an object in a uniform gravitational field and an object undergoing constant acceleration in the absence of gravity are under the same...
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  1. Home
  2. How Fair Is Vis?
  1. Home
  2. How Fair Is Vis?

Related Experiment Video

Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback
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How FAIR is VIS?

Daniel Wiegreffe, Christoph Garth, Guido Reina

    IEEE Computer Graphics and Applications
    |April 14, 2025

    View abstract on PubMed

    Summary
    This summary is machine-generated.

    The findable, accessible, interoperable, and reusable (FAIR) principles are crucial for scientific data. This study explores integrating FAIR principles into the visualization community by examining successful implementations in other fields.

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    Area of Science:

    • Data Science
    • Scientific Visualization
    • Information Management

    Background:

    • The findable, accessible, interoperable, and reusable (FAIR) principles are widely adopted across scientific disciplines for robust data management.
    • While many fields mandate FAIR principles, the scientific visualization community is actively developing strategies for their implementation.
    • Existing research highlights the importance of FAIR data for reproducibility and collaboration in scientific endeavors.

    Purpose of the Study:

    • To examine the intersection of the visualization community and FAIR data principles.
    • To identify successful FAIR principle implementations in other scientific disciplines.
    • To propose actionable recommendations for adopting FAIR principles within the visualization field.

    Main Methods:

    • Literature review of FAIR data principles and their application in various scientific domains.
    • Case study analysis of disciplines that have successfully integrated FAIR principles.
    • Comparative analysis to identify transferable strategies for the visualization community.

    Main Results:

    • Successful FAIR principle adoption in other fields offers transferable models for visualization.
    • Key challenges and opportunities for FAIR data implementation in visualization were identified.
    • Specific strategies for enhancing data findability, accessibility, and reusability in visualization were explored.

    Conclusions:

    • Integrating FAIR principles into the visualization community is feasible and beneficial.
    • Adoption of FAIR principles can enhance the rigor and impact of scientific visualization.
    • Further research and community engagement are recommended to fully realize FAIR data in visualization.