Description: "I'm from the government and I'm here to help you" takes on a sinister new meaning as jurisdictions around the world stumble over each other to 'set the people's data free'. New York City now has an Open Data Law and boasts in subway ads that 'our apps are whiz kid certified' (i.e. third party), which of course translates to 'we didn't pay for them, and don't blame us if somebody got it wrong and the bus don't come.' This session reports on my (and other people's) research aimed at prying out data that you're probably not supposed to have from Open Government Systems around the world. Recent findings from the Asia Pacific region are included.
"Torturing" a number of systems using off-the-shelf data analytic tools, and a bit of basic techno-wizardry (without breaking any laws), yielded some fascinating and unexpected information. Which union was shilling for political contributions for which candidate? Who has the most expensive home in town? Did a politician's wife vote for her own husband? An illustration of a shady "secondary industry" based on mining Open Government data will also be presented.
There are ways to build these systems well, and examples will be presented of the transformation from "terrible" to "not so bad." Applying classic computer science and accounting principles like 'least privilege' and 'segregation of duties' the presentation will suggest some ways to have our Open Data cake without letting data snoopers eat too much of it.
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