If you had to classify every shirt as a single colour, what information would you lose about each shirt?

A 10 minute talk with Catherine D’Ignazio on http://www.cbc.ca/radio/spark, worth a listen,— in order to co-construct Data collection, to represent the limitations of data, being willing to visualize what is NOT THERE

 If you had to classify every shirt as a single colour, what information would you lose about each shirt?

Picture by (flickr CC/Ewan Munro)

We live in an era of unequalled amounts of data. The Big Data age. And the sheer volume of it can be overwhelming. But no worries, you can look at a data visualization, and it will clear it all up. There’s a graph, or a chart or an infographic! Each an objective distillation of reality, right there in pictures. Only, what if those visualizations don’t tell the whole truth?

Catherine D’Ignazio is an Assistant Professor of Data Visualization and Civic Media in the Journalism Department at Emerson College in Boston. She thinks that we tend to accept data visualizations as facts because they seem to present an expert and neutral point of view.

But Catherine says that the perspectives of groups like women, minorities and others can often be excluded from what we consider objective data about the world around us. Which is why, earlier this year when this episode first aired, she posed the question, what would feminist data visualization look like?

The Interview is here: http://www.cbc.ca/radio/spark/307-snitching-stealing-exclusions-and-more-1.3414341/who-do-data-visualizations-leave-out-1.3414350?utm_content=buffere6850&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer

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