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Visualizing - Periscopic
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Description

ISOJ 2013

Transcript

  1. 1. Kim Rees, Periscopic @periscopic, @krees How to See DataMake Visualizations.
  2. 2. Kim Rees, Periscopic @periscopic, @krees How to See Data Kim Rees, Periscopic kim@periscopic.com @krees, @periscopic

Editor's Notes

  • If there’s one thing I can say it’s make visualizations. Period. I’ve only seen good things come of visualization. Yet we get so stymied with data visualization. It’s what I call “death by disclaimer” meaning you can get stuck in the details of data until you throw up your hands and give up. Do not succumb to that!
  • So first of all, the data is incomplete. Out of the gate, the data is incomplete. Florida doesn’t report.
  • We had to make many decisions when we sat down to make this visualization. First was the age prediction. Some people take issue with the veracity of this.
    I don’t think anyone would mistake this for a crystal ball.
  • 2013 is crowd-sourced data from Slate. A lot of questions arose when we considered adding this data. Data is completely different than 2010. Different source. But offered a look at suicide and accidents.
  • We chose to focus on victims. It’s emotional. But it’s a place we felt could be a bridge between sides on the gun control debate.
  • We, meaning you and I, we all live close to data. If you work with data, you are closer to the life of that data than anyone.... And when we get close to that life, to that underlying emotion and that context, that’s where we can make magic. That’s where we can transform that data into inspiration and ideas.

  • Description

    ISOJ 2013

    Transcript

    1. 1. Kim Rees, Periscopic @periscopic, @krees How to See DataMake Visualizations.
    2. 2. Kim Rees, Periscopic @periscopic, @krees How to See Data Kim Rees, Periscopic kim@periscopic.com @krees, @periscopic

    Editor's Notes

  • If there’s one thing I can say it’s make visualizations. Period. I’ve only seen good things come of visualization. Yet we get so stymied with data visualization. It’s what I call “death by disclaimer” meaning you can get stuck in the details of data until you throw up your hands and give up. Do not succumb to that!
  • So first of all, the data is incomplete. Out of the gate, the data is incomplete. Florida doesn’t report.
  • We had to make many decisions when we sat down to make this visualization. First was the age prediction. Some people take issue with the veracity of this.
    I don’t think anyone would mistake this for a crystal ball.
  • 2013 is crowd-sourced data from Slate. A lot of questions arose when we considered adding this data. Data is completely different than 2010. Different source. But offered a look at suicide and accidents.
  • We chose to focus on victims. It’s emotional. But it’s a place we felt could be a bridge between sides on the gun control debate.
  • We, meaning you and I, we all live close to data. If you work with data, you are closer to the life of that data than anyone.... And when we get close to that life, to that underlying emotion and that context, that’s where we can make magic. That’s where we can transform that data into inspiration and ideas.

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