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Graduate Student Data Visualization Award

Data Visualization Award

The University of South Carolina Libraries is pleased to announce the inaugural Graduate Student Data Visualization Award competition. The submission period has now closed for this year. Judging will take place in January 2024 with the award(s) being announced and presented during Love Data Week 2024 (Valentine's Day week). First place may be awarded up to $1000 with second and third place awards possible. 

This competition is designed to:

  • Highlight research by current University of South Carolina graduate students.
  • Celebrate excellence using data visualization to encourage and enhance knowledge explanation and comprehension.
  • Promote data literacy and effective data visualization creation and presentation.
  • Encourage awareness of data literacy services and resources provided by the University Libraries.

The Graduate Student Data Visualization Award offers USC graduate students the opportunity to show off their skills using data visualization in their research.  

Who is Eligible?

This competition is open to all currently registered University of South Carolina-Columbia graduate students. 

  • Entries must be original data visualization work.
  • Submissions are highly encouraged to use publicly available data.
  • Works created as part of a course assignment are permitted. 
  • Only one entry per person/group may be submitted.
  • Collaborative group submissions are permitted. A group award will be split evenly between the members of the group.

Types of Submissions

Data visualizations may include, but are not limited to, charts, graphs, plots, maps, histograms, etc. They can be static or dynamic.

Static data visualization examples include, but are not limited to:

  • A visualization for or from a research paper, report, or journal article you are currently working on or have produced in the past year. 
  • A visualization used within a research poster or infographic you produced for a conference or professional meeting.

Dynamic data visualization examples could include:

  • A research-based data visualization dashboard.
  • A research-based interactive or animated data visualization.

Evaluation Criteria

The evaluation process is focused solely on the data visualization submitted. We are not evaluating the larger research product within which the visualization exists. Judging will be based on success in conveying data-driven information in a visually meaningful and effective way. Judges will ask: 

  • Is the data visualization reliable? 
  • Does the visualization accurately convey the primary message of the data?
  • Is the visualization understandable to a non-specialist? 
  • Is the visualization intuitive?
  • If the visualization is dynamic, is movement within the work intuitive? 
  • Does the visualization offer a novel or enlightened way of conveying the data information?

We strongly encourage submissions using open and reproducible methods. 

Submissions will be evaluated, and awards will be determined, by University of South Carolina-Columbia faculty and staff possessing expertise in creating and assessing data visualization.  

Application Process

Graduate students may submit their visualization any time from Tuesday, September 5, 2023 to Friday, January 5, 2024. 

  • If the work is a static visualization for/from a paper or article, submit only the visualization.
  • If the work is a static visualization for/from a poster or infographic, submit only the visualization, not the full poster or infographic.
  • If the work is a dynamic dashboard, choose a single "view" for consideration. Dashboards with multiple panes are acceptable if the different panes show different facets of the same data.
  • If the work is an interactive or animated visualization, submit a single "view" for consideration along with a link to the full interactive or animated product.

as well as a brief essay detailing:

  • the purpose/goal of the visualization (why did you use a visualization?)
  • the visualization approach/type (why did you choose the particular chart/graph type?)
  • what visualization tool(s) you used and why you chose that tool