CHRGJ Co-Hosts Skills-Building Workshop Exploring Tableau Data Visualization


On Monday, April 4, the CHRGJ and Tandon School of Engineering co-hosted a workshop on Tableau Public, to train human rights practitioners in presenting their data in more convincing and visually appealing ways. This session was part of CHRGJ’s Data Visualization research project, which examines the ways in which human rights groups can use data visualization to enhance the impact and effectiveness of their research and advocacy.

In this project, CHRGJ is investigating ways in which human rights groups can use data visualization to enhance the impact and effectiveness of their research and advocacy. With a grant from the MacArthur Foundation, Professor Satterthwaite is collaborating with Professor Enrico Bertini and Professor Oded Nov of NYU-Poly as co-Primary Investigators to research different methods human rights groups are using to visualize their data and how this can be improved. Using the body of research resulting from the project, the team will develop guidelines to help human rights advocates use data visualization more effectively. The team will communicate these guidelines in a specially designed website and in-person at a series of trainings for researchers and advocates working on human rights.

The workshop was led by Dash Davidson, a data analyst at Tableau, who demonstrated ways to explore, understand and interact with data, and illustrated ways in which human rights practitioners can anticipate and react to this by employing  interactive data visualization strategies. Davidson provided several hands-on exercises, showing how various digital work packages can help practitioners bring data to life through visualization. Participants were coached in creating interactive dashboards, reports, charts, maps and real-time analysis on the basis of existing data, in ways that were directly relevant to participants’ daily work.

Davidson also discussed the relationship between, and advantages and disadvantages of, data visualization and storytelling. Together with an audience of students and practitioners, he sought to articulate this relationship more clearly and  walked the group through various scenarios in which one or the other might be more relevant.

He highlighted “data story” types for use when examining data and deciding how best to visualize data. These include change over time (from time series data), drilling down and zooming out (for when different conclusions can be drawn from data at higher level vs nuanced detailed viewing), contrast and intersections (to examine possible relationships within data), factors (to determine the various components of data), and outliers.

For more information about data visualization at CHRGJ, follow the  project website.


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