Another high energy OpenOakland event (23 Feb 13) in a nice new venue (the 81st Avenue Oakland Public Library). thanks to all who made it possible.
I’m putting my notes from the group focused especially on crime up here. i think i have wordPress configured so that you can comment on it (as soon as i approve it the first time) and all will be publically viewable We may decide to move these materials somewhere else, but to keep the great energy we had today I’ll start here.
OaklandWiki: Crime resources
Create an Oakland wiki resource page for crime related resources
Just in our first conversation in many references to information find
resources. These include better access to OPD’s web site information,
as well as other resources like Oakland’s Measure Y
Reach-out to Community-based crime groups
Things like Neighborhood Crime Prevention Councils (NCPCs)
(http://uncofo.com) and the Neighborhood Block Watch
organizations exist across much of Oakland. We need to develop a
technology resource that we can provide to these various
organizations. It could include things like:
- – basic hardware info: strong door locks, window security, etc. (eg,
Reed Brothers gave a great session at a recent neighborhood meeting at
the Dimond Library)
- – more exotic open source solutions to camera, motion sensors, (drones!?)
technologies that are becoming available
- nextdoor.com community building web tools (thanks Chris!); much better than Yahoo mailing lists!
- – coordinating picture exchanges among neighbors concerning crime events
- – coordination across block captains
- – anonymization of members’ contact information as requested: An
important feature mentioned by some participants is that some block
captains are reluctant to be publicly identified in these roles.
Much of the group’s attention was spent talking about data sets
generated by OPD and urban strategies Council. These feed into
requests for an API for new crime data provided by OPD in the future.
Add geocoding to OPD data
Several groups are pursuing the basic and critical task of producing a
table like the following from the OPD data
CASENUMBER,ADDRESS,Lat,Long 05-024771,8000 INTERNATIONAL BLVD,37.756228,-122.181777 05-024770,10300 INTERNATIONAL BLVD,37.740329,-122.167777 05-024777,8800 INTERNATIONAL BLVD,37.750728,-122.175577 05-024797,3400 FOOTHILL BLVD,37.782728,-122.220279
That is, given the CASENUMBER incident ID (primary key) for incidents
and their addresses in the OPD data, compute a latitude and longitude
to be associated with it.
An important idea that came up early (maybe because we had several
Google employees as part of our group!) was approaching Google
concerning the licensing rights to their Geocoder
(cf. https://developers.google.com/maps/documentation/geocoding/). If
we did a preliminary, proof of principle project with our Oakland
brigade, this would provide data for Google to evaluate as part of a
national relationship with Code For America.
It wouldn’t be bad if multiple people tackled this task, because
comparing across geo-servers would be illuminating.
The statute codes are appearing to be a key representation for crime
data. Eg, the USC data set has them but the OPD data does not.
Someone (who?!) is actively scraping textual passages associated with
statutes as a resource for further use
There are several “machine learning” tasks that are potentially useful
bits we can use on attributes in the USC data set to predict the
similar indicators in the OPD data set. Two specific tasks that would
- – OPD_CTYPE -> Statute
- – OPD_CTYPE -> USC_Indicators (eg, ‘Violence’, ‘Property’, ‘Homicide’,
‘Assaults’, ‘Robbery’, ‘Shootings’, ‘Burglary’,
‘MV_Theft’, ‘Rape’, ‘Weapons’, ‘Drugs’, ‘Sex’)