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Michael’s annotation that highlights the importance of whose voices are represented in the data strikes me as one of the key arguments D’Ignazio and Klein’s article Feminist Data Visualization. Because data collection is a process designed by the collector, it is inherently biased and controlled by the collector. This consequently limits the scope of the data to the resources possessed by the collector. Feminist theory in the context of data visualization aims to enlarge this scope to be as inclusive as possible by emphasizing the perspectives of many who have been marginalized and whose voices have historically been excluded. Yet, Klein and D’Ignazio recognize that even feminist theory runs into limitations when considering those who are gender non-conforming or transgender.

Michael notes how this question is a recurring theme in many of the articles we are reading.  This idea reminded me of the Han Rosling’s 200 Countries 200 Years video which briefly addressed the silencing of certain narratives through averages. For example, the video addressed the intersection of life expectancy and wealth by analyzing country averages for both categories. Rosling acknowledged that for certain countries, say China, when split into counties, had numbers that fell all over the graph and far from the average. Specifically, more rural provinces were poorer and had shorter life expectancies whereas Shanghai had higher levels of wealth and longer life expectancies. Rosling, the designer of the visualization, could have omitted dividing China into provinces and thus left out the voice of the poorer and more marginalized community. It was his choice to include such a narrative, but he only did so for China. Rosling therefore left many voices out of his data by using mostly averages per country.

Feminist Data Visualization aims to minimize the voices left out of data collection, making inclusive conclusions and visualizations.