Got the data. Now what?

[Casey Cora]

So, our CAR ace has put together a preliminary framework in Django, I've been collecting data on homicides in our area since the first of the year. We have several searchable, sortable categories (age, race, address, homicide location, etc. ) and subcategories (weapon, weapon type, relationship to suspect/victim, etc.) and so far, so good.

The idea is to build a page about homicides, and I've got tons of good story ideas because of it, both for print and multimedia.

But I'd to hate make all that data - all that potentially rich data - go to waste in some simple mashup map. Problem is, beyond number-crunching trend stories (middle-aged white females most likely to stabbed, etc.) I'm kind of at a loss on what that's going to be. I guess I'm really trying to avoid having 50-some pinpoints on a Google Map and leaving it at that. It's my first such project and I'm not sure how to go about that.

Anyone have any ideas?

Over on the Modern Journalist site, Brad King suggested a bunch of good stuff. Basically, using the map as a springboard for more involved stats, to wit:

property values in areas, money spent on cops for different areas, legislation that was passed by the city and where the money was spent, population decline, where campaign contributions came from, educational test scores...

Anyone else?

[Chris Amico]

One way to go with this is to start with the data, but then move away from numbers and focus on people, like the Oakland Trib did here or on neighborhoods. I used to work in the Antelope Valley (north of Los Angeles), and I can think of what the neighborhoods notorious for homicides looked like. There's a long trail of how those parts of the community got that way.