+ All Categories
Home > Documents > « Just Do It » A Parcel Data Integration Project WLIA Team Justin Conner, Wood County GIS...

« Just Do It » A Parcel Data Integration Project WLIA Team Justin Conner, Wood County GIS...

Date post: 29-Dec-2015
Category:
Upload: clifton-robinson
View: 213 times
Download: 0 times
Share this document with a friend
Popular Tags:
14
« Just Do It » A Parcel Data Integration Project WLIA Team Justin Conner, Wood County GIS Specialist Ian Grasshoff, Waupaca County GIS Coordinator/LIO Jeff DuMez, Brown County GIS Coordinator/LIO Bill Cozzens, Waukesha County Land Information Systems Analyst
Transcript

« Just Do It  »A Parcel Data 

Integration Project

WLIA TeamJustin Conner, Wood County GIS Specialist

Ian Grasshoff, Waupaca County GIS Coordinator/LIOJeff DuMez, Brown County GIS Coordinator/LIO

Bill Cozzens, Waukesha County Land Information Systems Analyst

Overview

• Brief Project Summary• Project Status• Data Gathering Process• Parcel Data Integration Methods• Parcel Data Issues• What’s Next?

Project Summary

• Goal– Single goal to collect as much parcel data as possible and

assemble the data into a single parcel dataset

• Purpose– The existing reality of statewide data is not tenable

• Created 25 years ago and needs to adapt to the 21st Century• Does not support Wisconsin as well as it should

– Demonstrate to other organizations, policy-makers and legislators the future of Wisconsin geographic information

• Modern, robust, comprehensive and easily accessible

Data Gathering

AirDropper

Data Gathering

AirDropper

Data Gathering

AirDropper

Data Gathering

AirDropper and DropBox

Project Status

• 62 of 72 counties sent data– Cities of Ashland and Eau Claire

• Of the 10 without parcels– 5 said “No thanks”– 5 were still hoping to hear from

• Aggregate Parcel Count as of 10/22/2012:

3,146,169

Parcel Data Integration Methods

Aggregate Parcel SchemaField Name Data Type

JDI_CTY_NAME Text(50)

JDI_PARCEL_ID Text(255)

JDI_OWN_LST Text(255)

JDI_OWN_FST Text(255)

JDI_OWN_LST_FST Text(255)

JDI_OWN_MAIL1 Text(255)

JDI_OWN_MAIL2 Text(255)

JDI_OWN_CITY Text(255)

JDI_OWN_ST Text(255)

JDI_OWN_ZIP Text(255)

JDI_PROPERTY_ADDR Text(255)

JDI_TX_CLASS Text(255)JDI_TX_LAND_VAL Double

Field Name Data Type

JDI_TX_IMP_VAL Double

JDI_TX_TOTAL_VAL Double

JDI_TX_ACRES Double

JDI_TX_YEAR Text(255)

JDI_CTY_DATE Date

JDI_PUB_DATE Date

JDI_URL Text(255)

Parcel Data Integration Methods

• Developed a python script tool to normalize and aggregate parcel data– A little additional data prep before running the tool– Python Script Tool Does the following:

• Adds the Just Do It (JDI) schema to the input parcel data• Transfers the input parcel attributes to the JDI schema• Converts input data to other data format (string -> integer etc)• Logs processing inputs and messages to an xml file• Appends the input parcel data to a Statewide parcel layer

– Very easy to repeat the process…

Parcel Data Integration Methods

Parcel Data Issues

• Attribute Issues (the major ones)– Working with “Flat Files” (data structured by line position)– Some data was all concatenated together (ex.  Owner First + Owner Last).  This mostly occurred with names and addresses.

– Concatenated values difficult to split out when a “space” was the only separator…

– Storing numeric data as mix of numbers and strings (ex. 40.12 acres).  You can’t do mathematical operations on text data..

– Storing substrings within strings (ex. Kevin “The Bear” Smith)– Assessment Classes & values combined vs. broken out– How Condo Parcels are handled (relationship vs. stacked)

Parcel Data Issues

• Geometry Issues (the major ones)– As you would imagine…gaps and overlaps do exist

At it’s widest point, approx. a 375 ft gap

At widest point, approx. a 307 ft

gap


Recommended