Back when I helped teach new data librarians about data, one of the themes my colleagues and I liked to repeat was that “data should tell a story.” By that we meant that raw facts are literally without meaning until we analyze them and understand the stories they tell. “Understanding” is more than facts. As John Seely Brown and Paul Duguid said in their book The Social Life of Information, “information” is something that we put in a database, but knowledge “is something we digest rather than merely hold. It entails the knower’s understanding and some degree of commitment. Thus while one person often has conflicting information, he or she will not usually have conflicting knowledge” (p 119-120).
In those early days of data-librarianship, the tools we had for finding and acquiring and using data were very primitive (and often expensive) compared to the tools available today. Today, one can download and install very sophisticated free software for statistical analysis, data visualization, and even data animation. And one can download enormous data time series directly from the web and do analysis on the fly.
One big source of data is, of course, the federal government. Of course, we shouldn’t just hope that the government will preserve and provide free access to its data. Libraries need to take action to ensure long-term free availability of data.
I say all that as an introduction to an article that I recommend to you as a source of inspiration toward action, an example of what can be done with government data today, and a cautionary tale of how data can be manipulated to tell stories that appear “true” but which actually distort the story the data really tell.
- 2016 Will Be The Warmest Year, But This Is How Deniers Will Spin It. Peter Aldhous. (December 20, 2016).
Aldhous provides code for using R and ImageMagick and Adobe Illustrator to load data on the average global temperature for each month since January 1880 directly from from the National Oceanic and Atmospheric Administration. He analyzes the data, animates it, and demonstrates how changing the timeline can make the data tell a false story.
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