Related Experiment Video
Updated: May 8, 2026
10:39
Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
Published on: August 29, 2025
Comparing the quality of crowdsourced data contributed by expert and non-experts
Linda See1, Alexis Comber, Carl Salk
1International Institute for Applied Systems Analysis, Ecosystem Services and Management Program, Laxenburg, Austria. see@iiasa.ac.at
Plos One
|August 13, 2013
Summary
Crowdsourced land cover data quality is comparable between experts and non-experts for human impact identification. However, experts show higher accuracy in identifying land cover types, suggesting targeted training is needed for crowdsourced environmental data validation.
Area of Science:
- Environmental Science
- Remote Sensing
- Geospatial Data Analysis
Background:
- Lack of in-situ environmental data hinders calibration/validation of remote sensing products and model development.
- Crowdsourcing offers a potential solution for increasing in-situ data supply.
- Concerns exist regarding the quality and usability of crowdsourced data in scientific research.
Purpose of the Study:
- To evaluate the quality of crowdsourced land cover data from Geo-Wiki.
- To determine differences in data quality between experts and non-experts in remote sensing.
- To assess the suitability of crowdsourced data for scientific research on land cover and human impact.
Main Methods:
- Analysis of crowdsourced land cover validation data from the Geo-Wiki tool.
- Comparison of accuracy between expert and non-expert contributors.
- Investigation of factors influencing data quality, such as consistency and confidence.
Main Results:
- Little difference in expert vs. non-expert identification of human impact.
- Experts demonstrated higher accuracy in identifying specific land cover types.
- Data accuracy improved with contributor consistency and self-reported confidence.
Conclusions:
- Crowdsourced data shows potential for land cover validation, with quality varying by task.
- Targeted training materials and feedback mechanisms are needed to improve non-expert contributions.
- Contributor consistency and confidence are valuable indicators for assessing crowdsourced data quality.
Related Concept Videos
01:22Estimating Population Mean with Unknown Standard Deviation
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the Guinness...
William S. Gosset (1876–1937) of the Guinness...
01:16Estimating Population Mean with Known Standard Deviation
To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate + error bound)
The...
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate + error bound)
The...
01:28Accuracy, limits, and approximation
Accuracy, limits, and approximations are common in many fields, especially in engineering calculations. These concepts are imperative for ensuring that a given value is as close as possible to its true value.
Accuracy is defined as the closeness of the measured value to the true or actual value. In engineering mechanics, repeated measurements are taken during theoretical or experimental analyses to ensure that the result is precise and accurate.
The accuracy of any solution is based on the...
Accuracy is defined as the closeness of the measured value to the true or actual value. In engineering mechanics, repeated measurements are taken during theoretical or experimental analyses to ensure that the result is precise and accurate.
The accuracy of any solution is based on the...
01:26Estimating Population Standard Deviation
When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
01:09Empirical Method to Interpret Standard Deviation
The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...
This rule is used widely in statistics to calculate the proportion of data values...
01:00Detection of Gross Error: The Q Test
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...