Mapping with

Google Fusion Tables

May 21, 2014

Welcome!

• Part 3 of a 3-part series

– Part 1: Intro to GIS Mapping (April 23)

– Part 2: Mapping in Google Fusion Tables (May 14)

– Part 3: Mapping in Google Fusion Tables (Today, May 21)

• Presenters – Christina Sanabria, LSC

– Brian Rowe, LSNTAP

• Recording will be available on LSNTAP’s

YouTube channel

• Phone lines are muted – please send questions

via chat

Today’s Objectives

1. How to map geographic areas (like counties

or zip codes).

2. Create a multi-layer map (a map that displays

two or more data sets at a time).

Number of Children in Foster Care, Ohio

• Counties represented

by dots

• Can’t see size, shape

or extent of the

county

The number of children placed in

substitute care by public agencies.

Source: Ohio Department of Job and

Family Services, via the Kids Count Data

Center

http://datacenter.kidscount.org/

Number of Children in Foster Care, Ohio

• Counties displayed

as polygons (shapes)

• See data more clearly

The number of children placed in

substitute care by public agencies.

Source: Ohio Department of Job and

Family Services, via the Kids Count Data

Center

http://datacenter.kidscount.org/

Polygon Maps with Fusion Tables

Any geographic region

• Counties, zip codes,

census tracts

To create a map like this,

we need a KML file with

county boundaries

What is a KML file?

.kml is a filetype

• Just like .doc is Word and .xls is Excel

• Tells Google where and how to draw geographic

regions

Familiar with GIS? .kml is Google’s version of.shp

files

Why do I need a KML?

A Fusion Table containing KML data can be

merged with other Fusion Tables.

• Upload KMLs to Fusion Tables

• Merge with statistical data to make maps that

display geographic areas

Where can I find KML files?

Tigerline (US Census)

• https://www.census.gov/geo/maps-data/data/tiger-

kml.html

• Counties and census tracts

GeoCommons

• http://geocommons.com/

• Many geographies, uploaded by community of users

Questions so far?

Project 1:

Elder Poverty in Ohio

Project 1: Elder Poverty in Ohio

Project goal:

Our Elder Law Taskforce is trying to plan for the upcoming

year and needs data to inform their process.

They want to know:

• Are there any geographic areas of concentration of elder

poverty?

• If so, where?

Project 1: Elder Poverty in Ohio

Project goal: Map elders in poverty by Census Tract

Project 1: Elder Poverty in Ohio

We’ll need to

• Structure information so we can map it

• Merge two Fusion Tables together (combine

poverty data + geographic data)

• Style the polygons with colors

• Set up a custom info window

• Share and publish the map

About Census Tracts

• Geographic region defined for the purpose of taking

a census.

• Smaller than a county, provide more granular data.

• Usually coincide with limits of cities, towns or other

administrative areas – homogeneous population.

• Frequently used.

Project 1: Gathering Poverty Data

American FactFinder

Data from Census, American Community Survey and more

http://factfinder2.census.gov/

FIPS Codes • Remember merging? We need a unique identifier (common,

standardized id) for our geographies in order to successfully merge

different tables.

• FIPS codes make good unique identifiers because they’re

consistent. Other terms have a lot of variation (St. John vs Saint

John).

FIPS code for each

census tract

FIPS Codes – Breaking it Down

39 = Ohio

001 = Adams County, OH

7701 = Census tract 7701

Complete code: 390017701000

Curious About FIPS codes in your Area?

Questions so far?

Columns for This Dataset

• Total population

• Total below poverty level

• Total Male below poverty

• below poverty - Male under 5 years

• below poverty - Male 5 years

• below poverty - Male 6 to 11 years

• below poverty - Male 12 to 14 years

• below poverty - Male 15 years

• below poverty - Male 16 and 17 years

• below poverty - Male 18 to 24 years

• below poverty - Male 25 to 34 years

• below poverty - Male 35 to 44 years

• below poverty - Male 45 to 54 years

• below poverty - Male 55 to 64 years

• below poverty - Male 65 to 74 years

• below poverty - Male 75 years and over

• Total Female below poverty

• below poverty - Female under 5 years

• below poverty - Female 5 years

• below poverty - Female 6 to 11 years

• below poverty - Female 12 to 14 years

• below poverty - Female 15 years

• below poverty - Female 16 and 17 years

• below poverty - Female 18 to 24 years

• below poverty - Female 25 to 34 years

• below poverty - Female 35 to 44 years

• below poverty - Female 45 to 54 years

• below poverty - Female 55 to 64 years

• below poverty - Female 65 to 74 years

• below poverty - Female 75 years and over

How to Aggregate these 4 Columns?

• Total population

• Total below poverty level

• Total Male below poverty

• below poverty - Male under 5 years

• below poverty - Male 5 years

• below poverty - Male 6 to 11 years

• below poverty - Male 12 to 14 years

• below poverty - Male 15 years

• below poverty - Male 16 and 17 years

• below poverty - Male 18 to 24 years

• below poverty - Male 25 to 34 years

• below poverty - Male 35 to 44 years

• below poverty - Male 45 to 54 years

• below poverty - Male 55 to 64 years

• below poverty - Male 65 to 74 years

• below poverty - Male 75 years and over

• Total Female below poverty

• below poverty - Female under 5 years

• below poverty - Female 5 years

• below poverty - Female 6 to 11 years

• below poverty - Female 12 to 14 years

• below poverty - Female 15 years

• below poverty - Female 16 and 17 years

• below poverty - Female 18 to 24 years

• below poverty - Female 25 to 34 years

• below poverty - Female 35 to 44 years

• below poverty - Female 45 to 54 years

• below poverty - Female 55 to 64 years

• below poverty - Female 65 to 74 years

• below poverty - Female 75 years and over

Using Formula Columns

We can use a formula column to perform math using data

from our dataset.

Our formula:

'below poverty - Male 65 to 74 years' + 'below poverty - Male 75 years

and over' + 'below poverty - Female 65 to 74 years' + 'below poverty -

Female 75 years and over'

• below poverty - Male 65 to 74 years

• below poverty - Male 75 years and over

• below poverty - Female 65 to 74 years

• below poverty - Female 75 years and over

Questions so far?

Project 2:

Affordable Housing Options for

Ohio’s Older Adults

Project 2: Affordable Housing for Ohio’s Older Adults

Project goal:

Housing is an area of law that impacts many older adults.

We want to analyze the availability of affordable housing

and compare to poverty rates.

They want to know:

• Are there sufficient affordable housing options

throughout the state?

• Is affordable housing located in areas with greatest

need?

Project 2: Affordable Housing for Ohio’s Older Adults

Project goal: Layer housing options over elder

poverty

Project 2: Gathering Data

“The Ohio Housing Locator is a free, searchable database of

affordable, accessible rental housing throughout Ohio.”

http://www.ohiohousinglocator.org/

Project 2: Layer Two Datasets into a Single Map

The Fusion Tables Layer Wizard

http://fusion-tables-api-

samples.googlecode.com/svn/trunk/FusionTablesLayerWizard/src/inde

x.html

Final questions?

Before you go…

We need to have a Data Pep Talk

Data Resources

American Community Survey

http://factfinder2.census.gov

Ohio Housing Locator

http://www.ohiohousinglocator.org/

“Data, Demographics, Statistics” resource list,

Legal Services Northern California

http://equity.lsnc.net/data-demographics-statistics/

Don’t be afraid to search!

Go Get Data!

• Start mapping your own data, or data from your local

partners

• Don’t be afraid to search!

– Online searches

– Seek out Open Data resources in your area

• Expect that the data will require some manipulation to be

“map ready”

• Bookmark and save useful data sources/ datasets

• Find something interesting? We’d love to know about it.

Any maps to share?

• At the end of last week, we challenged you to start

experimenting with maps in Google Fusion Tables.

• Does anyone have a sample map to share? Or any

questions that came up during that process?

Happy Mapping!

• Recordings are posted on LSNTAP’s YouTube channel

– Channel URL: https://www.youtube.com/user/NTAPvideos

– Session 1: Intro to GIS Mapping:

https://www.youtube.com/watch?v=qUQwSmIzzRo&list=UUa-

OqKCx5ruSg5MGzN187xQ

– Session 2: Intro to Google Fusion Tables:

http://www.youtube.com/watch?v=EvixbkSzFuQ&list=UUa-

OqKCx5ruSg5MGzN187xQ&feature=share

• Check in on LRI for new content

– New content is visible on the homepage: http://www.lri.lsc.gov

– Sign up for email updates to see new content:

http://www.lsc.gov/get-email-updates-lsc

• Questions? Got Stuck? Contact us!

– sanabriac@lsc.gov

– pellittierim@lsc.gov