This document describes how FME was used to clean and normalize postal address data from electoral lists for a political campaign. Addresses from four columns were normalized into a single schema using string processing tools like StringSearcher, AttributeSplitter, and AttributeManager. The normalized addresses can now be easily uploaded and used to update electoral lists as new information is received.

1. Postal address
clean-up
Andrew Zolnai, Richard Mosley

2. Andrew Zolnai
Support Specialist, Lead
Development at Safe Software
helped with this.
Richard Mosley
Geologist turned to GIS for over
30 years, covered all aspects of
geo-data, project and business
management in petroleum and
volunteered geography.

3. Two non-spatial Workbench uses:
1) postal address clean-up
2) & electoral list updates

4. Help French 2017
presidential / parliamentary
election campaign
Using nationbuilder.com
for a London UK based
campaign
Liste Electorale
Consulaire is structured but
inconsistent
Ergo normalise 4 address
columns into a schema
The premise

5. Regex on Steroids
1Spatial FME WT 2015:
scrape 4 years worth
of playlists and tracks
off the StrayFM
website
and categorise and
rank the most played
artists and tracks
Inspired usage here:
 StringSearcher
search address
components
 AttributeSplitter split
them into similar parts
 AttributeManager re-
order into one schema

6. Address normalization

7. Clean
Rinse
Repeat
Get the first matches of
address strings in the 4
address fields
If string is empty then
assign the next address
string to it
Country name is constant
last string
Build normalised string
sets backward from it
01
02
04
03

8. Address schema ready to upload

9. But that’s not all…
What about on-going updates to
Electoral Lists?

10. FeatureMerger non-spatial too!
Initial load:
 find rejected addresses
 repeat the procedure if possible
Ongoing updates:
 find the new entries as updated lists are received
 repeat the procedure on the “delta” only

11. Refresh mega-data lists

12. Place your screenshot here
Electoral lists for campaigns

13. Metadata is king
Data never come clean
Create schemas is key
Automate? Web service?
Tame
mega
lists

14. Thank you!
www.zolnai.ca
aiz@zolnai.ca