Search research articles

Related Concept Videos

Uncertainty: Overview

Uncertainty: Overview

In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.

Sources of Law

Sources of Law

Laws form the essential rules set by governing authorities to shape and control societal behavior. In nursing, laws guide actions, safeguard patient rights, define nurses' scope of practice, and maintain professional standards. Understanding the legal framework governing nursing involves recognizing four primary sources of law: constitutional, statutory, administrative (regulatory), and common law.
Constitutional law is foundational, deriving from federal and state constitutions, and...

Torts III

Torts III

Types of Quasi-intentional Torts in Healthcare
Quasi-intentional torts in healthcare involve acts where intent is not directed to harm an individual but results in harm due to careless or reckless speech.

Torts II

Torts II

Intentional torts in healthcare refer to deliberate actions that cause harm or infringe on the rights of others. Understanding these torts is crucial for healthcare professionals to avoid legal liabilities and maintain ethical standards in patient care.

Uncertainty: Confidence Intervals

Uncertainty: Confidence Intervals

The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...

Schemas

Schemas

A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.

You might also read

Related Articles

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

Sort by

Same author

A Supraparticle-Based Approach to Robust Biomimetic Superhydrophobic Coatings.

Small (Weinheim an der Bergstrasse, Germany)·2025

Same author

Prognostic value of non-invasive programmed ventricular stimulation after VT ablation to predict VT recurrences.

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing·2024

Same author

A screening for cerebral deoxygenation during VT ablations in patients with structural heart disease.

Clinical research in cardiology : official journal of the German Cardiac Society·2024

Same author

Deficiency of Nucleotide-binding oligomerization domain-containing proteins (NOD) 1 and 2 reduces atherosclerosis.

Basic research in cardiology·2020

Same author

Loss of cerebellar neurons in the progression of lentiviral disease: effects of CNS-permeant antiretroviral therapy.

Journal of neuroinflammation·2016

Same author

Adaptability and elasticity of the mixed lipid bilayer vesicles containing non-ionic surfactant designed for targeted drug delivery across the skin.

Journal of drug targeting·2008

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Jun 25, 2025

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Published on: February 16, 2011

Visualization as irritation: producing knowledge about medieval courts through uncertainty.

Silke Schwandt¹, Christian Wachter¹

¹Digital History, Department of History, Bielefeld University, Bielefeld, Germany.

Frontiers in Big Data

|May 27, 2024

Summary

This summary is machine-generated.

Visualizations in research can "productively irritate" existing knowledge by revealing unexpected patterns and creating uncertainty, leading to deeper scholarly insights. This approach enhances data interpretation, even with smaller datasets.

Keywords:

knowledge production semiotics theory uncertainty visualization

More Related Videos

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

Related Experiment Videos

Last Updated: Jun 25, 2025

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Published on: February 16, 2011

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

Area of Science:

Digital Humanities
Data Visualization
Scholarly Communication

Background:

Visualizations are key tools in data-driven research for knowledge production and communication.
Existing Digital Humanities (DH) discussions lack theoretical depth regarding visualization's objectivity and role in representing scholarly perspective and uncertainty.
Theoretical frameworks like semiotics and media modality are crucial for understanding visualization's potential in scholarly interpretation.

Purpose of the Study:

To establish a theoretical foundation for analyzing the role of visualizations in scholarly interpretation.
To introduce and explore the concept of "productive irritation" generated by visualizations.
To demonstrate how visualizations can foster innovation in research by challenging existing knowledge.

Main Methods:

Applying semiotic principles and media modality theories to the study of data visualizations.
Analyzing visualizations for their capacity to "productively irritate" scholarly knowledge.
Utilizing case studies from medieval English legal history to illustrate the concept.

Main Results:

Visualizations can "productively irritate" by presenting unexpected data patterns and by generating uncertainty about their own meaning.
This "productive irritation" stimulates deeper examination, questions about depicted information, and offers potential for greater insight.
The semiotic and semantic properties of visual media, particularly their holistic overview juxtaposed with semantic vagueness, facilitate multiple interpretations.

Conclusions:

Visualizations possess the capacity to "productively irritate" existing scholarly knowledge, driving innovation in interpretation.
The uncertainty inherent in visualizations is a valuable resource for scholarly interpretation, especially with complex big data.
The study highlights the potential of "productive irritation" below the big data level, rooted in visual media's semiotic properties, as evidenced in legal history examples.