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Open government is an incredibly popular topic today. From the appointment to office of the nation’s first chief data scientist, to cities like New York, San Francisco, and Chicago signing executive orders to open up city data to the public, more government data is available to us than ever before. Because of that, one would be right to think we’re in an era of unprecedented transparency.
Yet in late February 2015, investigative journalists revealed that the Chicago police department had been operating “black sites” around the city — essentially, places where Americans were detained, and then disappeared off the record. None of this data made it onto the city’s open data networks. This egregious, illegal behavior was not uncovered through open data, but through traditional journalistic methods.
This, and other stories like this, fundamentally calls into question the data integrity of open government initiatives. How can we still use this information to derive insights into our government? What can we do to identify omissions in the data? And how can we improve the integrity of open government data through traditional data analysis?.
KEYWORDS: government, data science, data analytics
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