Module 5 Conclusion

In this Session

  1. Content Review
  2. Resources
  3. References

5.1 Content Review

  1. Congratulations on completing the training materials. The content from this training package is intended to be an additional compilation of resources to aid you in your personal and professional endeavors to convey compelling visual stories from well-managed data sets. If you have any feedback or comments on this training that you’d like to share, please use this feedback survey.
  2. While the materials can be valuable for an individual, greater value can come from collaborating over these materials with colleagues with related roles throughout your organization. Remember that there are many roles in data science communication and the information passes through many phases and hands before ultimately getting to a target audience. Familiarity with your “data role,” and the role of your work partners will ultimately aid in the full data storytelling process.
  3. While this training can be an informative leap into data sciences, the greatest experience comes with repetitive practice on new topic areas. Consider these resources as a reference point to be reviewed intermittently when you need a reminder about key steps or best practices in managing, visualizing, or communicating data messages.

5.2 Resources

  1. The table below provides direct links to all of the files from each Module and Session. The full zipped package can be accessed and downloaded using this link.
Module Session Relevant Resources
  1. Data
  1. Data Management
  1. Data Cleaning
  1. Normalization and Standardization
  1. Tableau
  1. Tableau Basics
  1. Tableau Skills: Part 1
  1. Tableau Skills: Part 2
  1. Tableau Skills: Part 3
  1. Tableau Dashboards: Part 1
  1. Tableau Dashboards: Part 2
 
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  1. Publishing to the Web
  1. Storytelling
  1. Communication Principles
  1. Data Storytelling
  1. Working with Graphic Designers

5.3 References

  • Cash, David, William C. Clark, Frank Alcock, Nancy M. Dickson, Noelle Eckley, Jill Jäger. “Salience, Credibility, Legitimacy and Boundaries: Linking Research, Assessment and Decision Making,” KSG Working Papers Series, 2003. http://nrs.harvard.edu/urn-3:HUL.InstRepos:32067415
  • Lowndes, Julia S. Stewart, Benjamin D. Best, Courtney Scarborough, Jamie C. Afflerbach, Melanie R. Frazier, Casey C. O’hara, Ning Jiang, Benjamin S. Halpern. “Our Path to Better Science in Less Time Using Open Data Science Tools,” Nature Ecology & Evolution 1, 0160 (2017) https://doi.org/10.1038/s41559-017-0160
  • Borer, Elizabeth T., Eric W. Seabloom, Matthew B. Jones, Mark Schildhauer. “Some Simple Guidelines for Effective Data Management,” Bulletin of the Ecological Society of America 90, no. 2 (2009): 205–214. https://doi.org/10.1890/0012-9623-90.2.205
  • White, Ethan P., Elita Baldridge, Zachary T. Brym, Kenneth J. Locey, Daniel J McGlinn, Sarah R. Supp. “Nine Simple Ways to Make it Easier to (Re)use Your Data,” Ideas in Ecology and Evolution 6, no. 2 (2013): 1–10. https://doi.org/10.4033/iee.2013.6b.6.f
  • Hayden, Thomas, and Michelle Nijuis. The Science Writers’ Handbook: Everything You Need to Know to Pitch, Publish, and Prosper in the Digital Age. Da Capo Lifelong Books, 2013.
  • “COMPASS homepage,” accessed September 29, 2021, https://www.compassscicomm.org/