New Article: Three ways to be more equitable and inclusive with your data and data visualizations
Posted by Stanford Social Innovation Review on December 7, 2021
Through rigorous, data-based analysis, researchers and analysts can add to our understanding of societal shortcomings and point toward evidence-based solutions. But carelessly collecting and communicating data can lead to analyses and visualizations that have an outsized capacity to mislead, misrepresent, and harm communities already experiencing inequity and discrimination.
To unlock the full potential of data, researchers and analysts must consider and apply equity at every step of the research process. Ensuring responsible data collection, representing the communities surveyed accurately, and incorporating community input whenever possible will lead to more equitable data analyses and visualizations. Although there is no one-size-fits-all approach to working with data, for researchers to truly do no harm, they must build their work on a foundation of empathy.
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