NNLM Data Visualization Challenge

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The NNLM Data Visualization Challenge, hosted by the National Evaluation Center for the NNLM, will provide inspiration, reveal insights, and showcase skills in visualizing open datasets. The Challenge encourages participants to push the boundaries of their skills by testing out new tools, techniques, or approaches, and publicly demonstrating their best visualizations.  

Read more about incredible 2023 awardees and see the 2023 awardee visualizations in Zenodo.

Submissions have now closed for the 2024 NNLM Data Visualization Challenge. However, we extend a warm invitation for you to participate once again when the event returns in 2025.

 

Overview

The NNLM Data Visualization Challenge allows you to:  

  • Showcase an open dataset. You can use one or more sources of data that is openly available, such as Data.gov, Kaggle.com, Census.gov.
  • Focus on any audience. You can focus your efforts on designing visualizations for one or more audiences, such as policy makers, faculty and administration, or the public.
  • Use your choice of tools. You can use one or more tools, such as: Excel, Tableau, Google Charts, PowerBI, and programming languages/libraries such as R, Python, SPSS, SAS.

Submissions can be static, or dynamic, such as animated, or web-based interactive stories and may include, but are not limited to maps, charts, graphs, data art, figures from papers or posters, infographics, and data dashboards. Submissions should be submitted as a file (pdf, png, etc.) or link (url, github page, etc.).  Any submissions will be shared in an open gallery in an online repository. The top visualizations will be given $500 awards to be used for professional travel, presentation at a conference, open access publishing, or skill development related to data visualization.

If you have any questions or trouble uploading your submissions please reach out to the National Evaluation Center at nec-dataviz@northwestern.edu

 

Awards

Audience

You can focus your efforts on designing visualizations for one or more audiences, such as policy makers, faculty and administration, or the public.              
 

Single Data Visualization (static or dynamic)

A singular data visualization that is either static or dynamic (i.e. a map, graph, chart or diagram).  

  • First Place: $500 
  • Bright Future Award: $500 

 

Complex Data Visualization (static or dynamic)

A complex data visualization, such as an infographic or dashboard, often contains multiple data visualizations and may also contain narrative and graphics. 

  • First Place: $500 
  • Bright Future Award: $500 

 

Judges

We welcome our three judges who review submissions and decide on the top awards:  

  • Kimberly Thomas is the Strategic Evaluation Officer for the National Library of Medicine (NLM) at the National Institutes of Health. She is a 20+ year public health scientist and in her role as NLM’s Evaluation Officer she provides a broad range of programmatic evaluative expertise, leadership, and coordination to help the NLM better understand performance, impact, and alignment of efforts relative to the strategic goals. She advises on and conducts evaluations and analyses across NLM, as well as collaborates on evaluative efforts at the trans-NIH level, such as those assessing NIH’s UNITE initiative and NIH evaluation capacity in response to the Evidence Act. Prior to coming to the NIH a few years ago, Kimberly spent 17 years at the Centers for Disease Control & Prevention using data to drive action and inform decisions at the national level for programs with funding ranges $30 million - $1 billion (opioids overdose prevention). Kimberly’s connection to data visualization comes as a direct and key component of presenting and sharing data findings with local and state partners and various elected officials at the county, state, and federal levels and leading efforts to develop web-based tools to facilitate on-demand data reviews for organizational leadership.
  • Sally Gore MS, MS LIS, is the manager of Research and Scholarly Communication Services for the Lamar Soutter Library, University of Massachusetts Chan Medical School. In this role, she oversees the Library's collaborative efforts with basic science and clinical researchers on campus, including expanding support and instruction in data services. Her department leads all scholarly communication endeavors for the Library, including providing bibliometric analysis, tracking research impact, assisting PIs in achieving compliance with funder-based mandates, promoting open science initiatives, and managing eScholarship@UMassChan, the University's institutional repository. Sally also serves as the Associate Editor of the Journal of eScience Librarianship.
  • Marci Bradenburg is the Bioinformationist at the University of Michigan Taubman Health Sciences Library. She works closely with the Department of Computational Medicine & Bioinformatics (DCM&B) and the BRCF Bioinformatics Core, in addition to supporting other bioinformatics research on campus.  She is part of the Library's visualization services team, providing instruction and consultation on several visualization resources, such as Cytoscape. She received her Masters in Biology from Ohio University and Masters in Information from University of Michigan. Prior to working at the University of Michigan, she was the Biosciences Informationist at the National Cancer Institute-Frederick in Frederick, MD.

 

Timeline

All dates are approximations. The National Evaluation Center (NEC) reserves the right to change dates as needed. Participants will be notified of date changes on this website. 

  • Submissions open by 10 am (Central Time) on February 1, 2024 (Thursday) through 3 pm (Central Time) on April 12, 2024 (Sunday)  
  • Award notifications will be sent to the NNLM Network by end of April 2024  
  • Visualizations available for public viewing in open repository collection by early May 2024  
  • Awards must be spent by February 2025 

 

Rules 

Eligibility
  • Eligibility is open to anyone in the United States, who is at least 18 years old, and who has taken part in NNLM activities (e.g., training, events, or funding). We also encourage health sciences library staff, health sciences librarians working in non-library settings, library students, or staff members from NNLM Regional Medical Libraries, Offices, or Centers to apply.  
  • Awards are restricted to individuals who are 18 years or older and based in the United States.  
  • Collaborations are welcome but any award will be granted to the individual person submitting the entry. Any group entry should include the list of contributor names.  
  • Members of the National Evaluation Center are not eligible to win awards. However, they may enter visualizations that can be included in the full gallery housed in an online repository.  

 

Submissions
  • Only one submission per individual or group is allowed for either or both categories (e.g Single Data Visualization or Complex Data Visualization)  
  • Any work presented must be your original creation and be fully owned by you. 
  • Your submission must not supply untruthful, incomplete, inaccurate or misleading information.  

 

Datasets

 

Awards
  • Submissions will be judged separately for first place and the Bright Future Award. The Bright Future Award is given to submissions from beginners or advanced beginners in data visualization who show promise in their work and dedication to improving their skillset over time. 
  • The National Evaluation Center reserves the right to not provide an award for any category.  
  • Awards are restricted to individuals who are 18 years or older and based in the United States. 
  • Collaborations are welcome but any award will be granted to the individual person submitting the entry. Any group entry should include the list of contributor names. 
  • Awards must be spent by February 2025 and used only for professional travel, presentation at a conference, open access publishing, or skill development related to data visualization. Any travel funds must be spent for travel only within the U.S.  
  • Each submission can contain a basic budget for the award. You DO NOT need to attach an award budget to the submission. If your submission is selected to receive the First Place or Bright Futures Award, you will need to provide the National Evaluation Center (NEC) with a simple budget (see template here) that includes information about how you will spend the award. 
  • Please note that we will blind your submission (as much as reasonably possible) for the judges by removing identifiers such as affiliations, locations, etc.

 

Licensing terms
  • By entering you give the National Evaluation Office the non-exclusive right to publish your work and/or screenshots of it for social media, on websites, in emails and reports, and well as deposit your submission into an online repository. Any such communications about the contest entries or winners will properly attribute the creator(s) of the work.  
  • Submissions will be made openly available in an online repository.  You must choose a Creative Commons License for your work.  
  • If submitting a dynamic file, please note that for any winning visualizations we will eventually need a static version (such as a screenshot) to display in an online repository.

 

How to Submit 

A link to an online submission form will be provided here.   

  • Submissions open: 10 am (Central Time) February 1, 2024 (Thursday) 
  • Last day for submissions: 3 pm (Central Time) April 12, 2024 (Sunday) 

Submissions should be submitted as a file (pdf, png, etc.) or link (url, github page, etc.). If you have any questions or trouble uploading your submissions please reach out to the National Evaluation Center at nec-dataviz@northwestern.edu 

 

The online submission form has these fields:           
*asterisk represents required responses 

*Please enter your full name. (Collaborations are welcome but only one individual can submit.) 

*Please enter your email address. 

Please enter your institutional affiliation (if applicable). 

*What category is this submission for?         
(You may enter only one visualization per category.)   

  • Single Data Visualization (static or dynamic) 
  • Complex Data Visualization (infographic or dashboard) 

*Title of data visualization.  

*Name and description of Data Source(s).

*Abstract (Limit to 500 words, not including references) Includes: 

  • Description  
  • Data Source(s)  
  • Visualization tool(s) used  
  • Intended Audience  
  • References (as needed) 

Submission File (up to 1GB). Content options are PDF, Document (DOC, DOCX, TXT, ODT), Spreadsheet (CSV, XLS, XLSX, ODS), or Graphic (JPG, PNG, GIF). 

Submission Link (for files over 1GB, web or interactive submissions). 

*Years of experience with data visualization (approximation) 

  • Beginner (0-3 years) 
  • Proficient (4-5 years) 
  • Expert (6 years and beyond) 

Submit award budget 

You DO NOT need to attach an award budget to this submission. If you have the award budget ready to submit, you may submit it now. 

If your submission is selected to receive the First Place or Bright Futures Award, you will need to provide us with a simple budget (see template - Budget Template for Data Viz Challenge.xlsx) that includes information about how you will spend the award. 

  • Awards must be spent by February 2025 and used only for professional travel, presentation at a conference, open access publishing, or skill development related to data visualization. 
  • Any travel funds must be spent for travel only within the U.S.  
  • Collaborations are welcome but any award will be granted to the individual person submitting the entry. 

*I agree.        
I am eligible to apply to the NNLM Data Visualization Challenge. Eligibility includes anyone in the United States, who is at least 18 years old, and who has taken part in NNLM activities (e.g., training or grant programs), any health sciences library staff, health sciences librarians working in non-library settings, library students, or NNLM staff members.    

  • My submission is my original creation and is fully owned by me.  
  • My submission does not supply untruthful, incomplete, inaccurate or misleading information. 
  • My submission includes data I have the rights to use. The dataset is publicly available at no-cost and does not contain data that should remain confidential or private.  

Distribution License and Deposit Agreement

I grant the Network of Libraries of Medicine (NNLM) a non-exclusive license and royalty-free permission to distribute and use my submission and accompanying text in perpetuity in their original forms and/or modified forms to: 

  • promote the visualization challenge, 
  • deposit into an online repository, 
  • and highlight projects taking place for the NNLM. 

I have the necessary rights, permissions, and/or licenses to grant the NNLM these rights. I understand that this means that my submission and accompanying text in its original forms and/or modified forms, may be incorporated in any and all media. I understand that my submission and accompanying text will be deposited as an open access record with public visibility (for both metadata and associated files) in an online repository. 

If I wish to revoke permissions to use my submission and accompanying text, I must do so in writing to NNLM. By accepting this agreement, you still retain copyright to your submission. The NNLM will clearly identify your name as the creator and will not make any alteration, other than as allowed by this license, to your submission and accompanying text.      

By accepting this license, you acknowledge that you have read and agreed to the terms of this agreement and all related NNLM policies.

*Creative Commons Licensing. Creators must choose a creative commons license for their submissions and accompanying texts.  

  • CC BY: This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. 
  • CC BY-SA: This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator and they must distribute their contributions under the same license as the original. This license allows for commercial use.  
  • CC0 (aka CC Zero) is a public dedication tool, which allows creators to give up their copyright and put their works into the worldwide public domain. CC0 allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, with no conditions. 
  • Other:  [enter text]

 

Evaluation Criteria

The submissions will be evaluated by data visualization challenge the National Evaluation Center. Submissions will be evaluated on the ability to convey information in a meaningful and aesthetically appealing way. When developing a submission, participants should consider the following: 

  1. Data sources: accurate data and from an open and reliable source.  
  2. Abstract: The abstract includes all required content and provides a very clear description of the visualization to gain a comfortable understanding of the topic.  
  3. Content: The visualization has a very clear purpose (i.e. shows meaningful relationships or patterns between the data) and supports the overall theme.  
  4. Data: The visualization fits the data very well and makes it easy to interpret. 
  5.  Aesthetics: The visualization is exceptionally attractive in terms of design, layout, and neatness, which means white space, graphic elements and/or alignment are used effectively to organize material. Choice and application of color shows an advanced knowledge of color relationships. Color choice greatly enhances the idea being expressed. 
  6. Annotation: Title(s) are creative and clearly relates to the visualization(s), no misspellings or grammatical errors. Labels for axes and/or data points are exceptional and strongly enhance the viewers understanding of the visualization, no misspellings or grammatical errors. Legend(s) greatly enhance the interpretation of visualization(s). The legend is necessary and present, easy-to-find and read, and contains a complete set of symbols, units, or other necessary information. 
  7. Audience: The visualization shows strong awareness of the target audience(s) and very clearly adapts the design and description to the target audience(s) to influence attitude or actions. For example, novices will expect visualizations to help with general understanding of topic(s), whereas experts will expect visualizations to help with investigation and discovery of topic(s). 

 

Questions? 

Contact: National Evaluation Center at nec-dataviz@northwestern.edu 

 

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last updated: 04/16/24 17:11