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Bar Graph01:07

Bar Graph

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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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Ogive Graph01:07

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An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
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Pareto Chart00:52

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A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the lines represent the cumulative total values. In this chart, the longest bars are arranged on the left and the shortest bars on the right, which makes it easier to read and interpret the data. It can also be called a Pareto diagram or Pareto analysis.
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Multiple Bar Graph01:07

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Related Experiment Video

Updated: Sep 2, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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A Scholarly Knowledge Graph-Powered Dashboard: Implementation and User Evaluation.

Olga Lezhnina1, Gábor Kismihók1, Manuel Prinz2

  • 1Learning and Skill Analytics Research Group, TIB-Leibniz Information Centre for Science and Technology, Hannover, Germany.

Frontiers in Research Metrics and Analytics
|August 5, 2022
PubMed
Summary
This summary is machine-generated.

We developed a new dashboard to visualize research contributions using scholarly knowledge graphs. This tool enhances user experience and promotes wider adoption of these advanced information retrieval methods in academia.

Keywords:
ORKGdashboardscholarly communicationscholarly knowledge graphuser evaluation

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Area of Science:

  • Computer Science
  • Information Science
  • Educational Science

Background:

  • Scholarly knowledge graphs offer a new way for researchers to find information.
  • Wider use of these graphs aids in digitalizing publications and advancing scholarly communication.
  • Current interfaces may not fully leverage the potential of knowledge graphs for user engagement.

Purpose of the Study:

  • To increase the acceptance and usability of scholarly knowledge graphs.
  • To present a novel dashboard visualizing research contributions within the Open Research Knowledge Graph (ORKG).
  • To improve the user experience of interacting with scholarly knowledge graph data.

Main Methods:

  • Developed a multi-relational visualization tool by integrating perspectives from computer science, graphic design, and human-technology interaction.
  • Focused on visualizing research contributions within the educational science domain using the ORKG framework.
  • Conducted a user evaluation survey to assess the dashboard's appeal and usability.

Main Results:

  • Preliminary user evaluation indicates the developed dashboard is perceived as more appealing than the baseline ORKG interface.
  • The visualization tool successfully represents complex research contributions.
  • The dashboard design positively impacts user perception and engagement.

Conclusions:

  • Scholarly knowledge graph-powered dashboards can significantly enhance user experience and acceptance.
  • The developed visualization approach offers a versatile model for various research domains.
  • Findings support the broader integration of knowledge graphs into scholarly communication and research practices.