Open data is on the rise, and freely available data sets - like municipal data - can bring huge value and new features to applications, at no upfront cost. For example, open crime data can be leveraged to support features that make location based apps safer for users.
However, the challenge for developers is to efficiently wrangle, store and deliver open data sets without having to build complex data architectures.
Using the example of crime data applied to a new safety feature for Pokemon Go, this webinar will demonstrate how to harvest open geo data, store it natively in a cloud database (Cloudant), and ensure it is highly available for applications and analytics platforms.
Gen AI in Business - Global Trends Report 2024.pdf
Optimizing location-based apps with open data
1. IBM Cloud Data Services
Optimizing Location Based Apps
with Open Data
Raj Singh, PhD
Developer Advocate: Geo | Open Data
rrsingh@us.ibm.com
http://ibm.biz/rajrsingh
twitter: @rajrsingh
2. @rajrsingh
IBM Cloud Data Services
Read my newsletter on open data!
http://opendatamag.rajsingh.org
My background
Developer Advocate, Geo + open data
IBM Analytics
MCP, Ph.D.
Urban Studies & Planning
Crime data blog hot off the presses
https://developer.ibm.com/clouddataservices/2016/11/03/open-crime-data
3. @rajrsingh
IBM Cloud Data Services
Agenda
• Finding and harvesting open crime data
• Data wrangling & schema reconciliation
• Products
• data service
• safety app
7. @rajrsingh
IBM Cloud Data Services
Where to find open data
US
• http://us-city.census.okfn.org
UK crime data:
• https://data.police.uk/data/
Europe
• https://data.europa.eu/euodp/en/data
• https://www.europeandataportal.eu/
9. @rajrsingh
IBM Cloud Data Services
Data
Wrangling
Gaucho Data Wrangler. Picture by Dave Werkley, http://compendiumofcountries.org/wiki/index.php?title=File:Data_Wrangler_-_Gaucho.png
11. @rajrsingh
IBM Cloud Data Services
Querying Socrata for Boston Crimes
• https://data.cityofboston.gov/resource/29yf-ye7n.json?
$where=
occurred_on_date>=“2016-08-23” AND
occurred_on_date<“2016-08-24”
• Then run it every day…
13. @rajrsingh
IBM Cloud Data Services
Crime reconciliation
• CDSNV: non-violent
• CDSDV: domestic
violence
• CDSSTREET: street crime
14. @rajrsingh
IBM Cloud Data Services
Data
Products &
Offerings
By Patrick Denker from Athens, GA - DSC04878, CC BY 2.0, https://commons.wikimedia.org/w/index.php?curid=37301184
19. @rajrsingh
IBM Cloud Data Services
Safety app architecture
1. Built using Ionic framework
2. Cloudant -> mobile replication
3. Safety rating decision
4. Notification
https://github.com/ibm-cds-labs/crionic | by Jason Smith
20. @rajrsingh
IBM Cloud Data Services
Safety app phase 2
• Add Census demographics
• Population: crimes per capita
• Housing quality
• Add Points of Interest
• Commercial activity: busy areas are safer
21. IBM Cloud Data Services
Raj Singh
Developer Advocate: Geo | Open
Data
rrsingh@us.ibm.com
http://ibm.biz/rajrsingh
Twitter: @rajrsingh
LinkedIn: rajrsingh
Thanks
• REST API
• http://ibm.biz/opencrimes
• Crime demos
• http://crimedemos.mybluemix.net/crimebrowser
• http://crimedemos.mybluemix.net
• Crime code reconciliation tables
• https://github.com/ibm-cds-labs/open-data/tree/master/crime
• Harvesting service code
• https://github.com/ibm-cds-labs/crimeharvest
• IBM Cloud Data Services on Bluemix
• http://www.ibm.com/cloud-computing/bluemix/solutions/data-analytics/
Editor's Notes
http://us-city.census.okfn.org
http://us-city.census.okfn.org/place/sanfrancisco
https://data.police.uk/data/ by 2011 lower layer super output area (LSOA)
https://data.cityofboston.gov/Public-Safety/Crime-Incident-Reports-August-2015-To-Date-Source-/fqn4-4qap
Nice standardized UI for the common person to browse, query and visualize data
Provides a SQL-like query language for developers
But it’s only as good as the data cities put in it…
No standard for coding
No standard for release schedule
Varying location accuracy (points, slightly generalized points, blocks, etc)
https://en.wikipedia.org/wiki/Intermodal_container
By Patrick Denker from Athens, GA - DSC04878, CC BY 2.0, https://commons.wikimedia.org/w/index.php?curid=37301184
I’ve been looking at crime data for a while, but my interest took on a new intensity when Pokémon Go came out and we started hearing about people luring players into dark alleys and robbing them. Surely data could play a role in helping people avoid these incidents.
But it could also be used for so much more: Should I open a store here? If I do, when should it close?
So I decided I would build an app that let you know when you were heading towards an area that, based on crime data, looked like a bad bet.