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

One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

3.4K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
3.4K
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

6.8K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
6.8K
Convenience Sampling Method00:55

Convenience Sampling Method

9.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
9.0K
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

54
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
54
Manipulation and Analysis01:21

Manipulation and Analysis

48
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
48
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

442
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
442

You might also read

Related Articles

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

Sort by
Same author

Metabolic Reprogramming-Driven Lactylation: Emerging Mechanisms Linking DNA Damage Repair and Chemoresistance in Cancer.

Cells·2026
Same author

From Verbal Reports to Personalized Activity Trackers: Understanding the Challenges of Ground Truth Data Collection with Older Adults in the Wild.

Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies·2026
Same author

Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Users.

Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference·2026
Same author

Mettl3-Mediated m6A Methylation of Pdgfrb Regulates the Angiogenesis-Dependent Bone Formation.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology·2026
Same author

Exploring Collaboration to Center the Deaf Community in Sign Language AI.

ASSETS. Annual ACM Conference on Assistive Technologies·2026
Same author

Enabling Older Adults to Provide High-quality Activity Labels: Unpacking Accuracy, Precision, and Granularity in Activity Labeling.

Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies·2026
Same journal

Beyond Beautiful: Embroidering Legible and Expressive Tactile Graphics.

ASSETS. Annual ACM Conference on Assistive Technologies·2026
Same journal

"Better Than Nothing" or Not Enough? User-Centered Reflections on AI-Generated Audio Descriptions Across Media Formats.

ASSETS. Annual ACM Conference on Assistive Technologies·2026
Same journal

DescribePro: Collaborative Audio Description with Human-AI Interaction.

ASSETS. Annual ACM Conference on Assistive Technologies·2026
Same journal

Minor Resistance: The Everyday Politics and Power Dynamics of Assistive Technology Adoption.

ASSETS. Annual ACM Conference on Assistive Technologies·2026
Same journal

Co-Designing Culturally Grounded Mobile Health Games for Hypertension Management in Indigenous Communities.

ASSETS. Annual ACM Conference on Assistive Technologies·2026
Same journal

Modeling Accessibility: Characterizing What We Mean by "Accessible".

ASSETS. Annual ACM Conference on Assistive Technologies·2026
See all related articles

Related Experiment Video

Updated: Aug 6, 2025

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
06:26

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI

Published on: November 27, 2019

71.9K

Data Representativeness in Accessibility Datasets: A Meta-Analysis.

Rie Kamikubo1, Lining Wang2, Crystal Marte1

  • 1College of Information Studies, University of Maryland, College Park, United States.

ASSETS. Annual ACM Conference on Assistive Technologies
|March 20, 2023
PubMed
Summary
This summary is machine-generated.

Accessibility datasets show diverse age representation but lack gender and race diversity. Improving data collection is crucial for inclusive artificial intelligence (AI) and mitigating bias for marginalized groups.

Keywords:
AI FATEAccessibilityAgeGenderHuman-centered computing → Human computer interaction (HCI)Race and ethnicitySocial and professional topics → People with disabilitiesaccessibilityagingdatasetsdiversityinclusionrepresentation

More Related Videos

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.5K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.6K

Related Experiment Videos

Last Updated: Aug 6, 2025

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
06:26

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI

Published on: November 27, 2019

71.9K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.5K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.6K

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Ethical concerns arise from unfair outcomes in data-driven systems impacting marginalized groups.
  • AI fairness and inclusion efforts necessitate representative datasets across demographic groups.
  • Accessibility datasets, sourced from people with disabilities and older adults, are vital for inclusive AI applications.

Purpose of the Study:

  • To analyze the representativeness of age, gender, and race/ethnicity in accessibility datasets.
  • To identify demographic gaps within datasets crucial for mitigating AI bias.
  • To explore challenges in classifying sensitive demographic variables within these datasets.

Main Methods:

  • Reviewed publicly available information from 190 accessibility datasets.
  • Examined demographic data focusing on age, gender, and race/ethnicity.
  • Investigated the consistency and source of demographic variable classification.

Main Results:

  • Accessibility datasets demonstrate diverse age representation.
  • Significant gaps were found in gender and race/ethnicity representation.
  • Classification of demographic variables like gender and race/ethnicity is inconsistent and often lacks a known source.

Conclusions:

  • Accessibility datasets require improved gender and race/ethnicity representation for equitable AI.
  • Challenges in demographic data classification hinder accurate bias assessment.
  • Efforts to enhance representation of disabled data contributors are essential for inclusive AI systems.