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Related Concept Videos

Pie Chart01:04

Pie Chart

13.0K
A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each indicating numerical proportions. It is also used to show the relative sizes of data in a single chart.
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
13.0K
Bar Graph01:07

Bar Graph

17.2K
A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
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Modified Boxplots00:57

Modified Boxplots

8.0K
A standard box and whisker plot informs us about the spread of the data in a given sample. One can identify the minimum value, maximum value, first quartile value, second quartile or median value, and third quartile.
However, the box plot does not tell the reader about outliers - values that lie far from the center of the data. We can modify the standard box and whisker plot to identify the outliers and visualize the actual spread of the data in a sample.
Initially, we calculate the adjusted...
8.0K
Multiple Bar Graph01:07

Multiple Bar Graph

6.3K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
6.3K
Review and Preview01:13

Review and Preview

9.5K
Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
9.5K
Review and Preview01:10

Review and Preview

5.9K
In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
5.9K

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Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
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Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

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Harnessing modern web application technology to create intuitive and efficient data visualization and sharing tools.

Dylan Wood1, Margaret King1, Drew Landis1

  • 1The Mind Research Network and LBERI Albuquerque, NM, USA.

Frontiers in Neuroinformatics
|September 11, 2014
PubMed
Summary
This summary is machine-generated.

Neuroscientists can now access and explore large neuroimaging datasets more easily. A new web application, COINS Data Exchange, simplifies big data sharing for scientific discovery.

Keywords:
big datadata sharingjavascriptneuroinformaticsopen neurosciencequery builder

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Area of Science:

  • Neuroscience
  • Data Science
  • Bioinformatics

Background:

  • Neuroscience research generates big data, posing challenges for collection, organization, and analysis.
  • Existing web technologies can improve information sharing and access in scientific communities.

Purpose of the Study:

  • To present a web application, the COINS Data Exchange, for facilitating neuroimaging data sharing.
  • To detail the Exploration phase of the COINS Data Exchange, focusing on intuitive data access.

Main Methods:

  • Utilized web application technologies like RESTful webservices, HTML5, and JavaScript.
  • Implemented asynchronous client-server communication (AJAX) for responsive data exploration.
  • Developed a framework with an API for data exploration by users and other applications.

Main Results:

  • The COINS Data Exchange enables users to explore and request complex neuroimaging datasets.
  • The Exploration phase focuses on intuitive access to large datasets.
  • Since August 2012, the platform has provided over 2500 GB of data to researchers.

Conclusions:

  • Web application technologies can significantly lower hurdles in big data management for neuroscientists.
  • The COINS Data Exchange enhances data sharing within the neuroimaging community.
  • The platform's design supports efficient exploration and access to valuable research data.