Property Data Learning Circle

Western Pennsylvania Regional Data Center/Carnegie Library of Pittsburgh

Data about properties is incredibly valuable in developing neighborhood plans and redevelopment strategies. Data at the property level has also been used to target interventions and investments within a neighborhood. To build the capacity of neighborhood stakeholders, The Western Pennsylvania Regional Data Center and the Carnegie Library of Pittsburgh are collaborating to offer a learning circle to provide hands-on training and support to people that want to use property data to understand more about their communities. We’ll be using Alan Mallach’s <A HREF="http://action.communityprogress.net/p/salsa/web/common/public/signup?signup_page_KEY=10601" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">“Neighborhoods by Numbers, an Introduction to Finding and Using Small Area Data”</A> as a companion guide to the course.
 By participating in the four-session learning circle, participants will learn how to: 
<UL>
<LI>
Organize and conduct neighborhood property surveys 
</LI>
<LI>
Create tables and charts based on neighborhood statistics 
</LI>
<LI>
Make sharable, interactive property maps using open data 
</LI>
<LI>
Tie data to neighborhood redevelopment strategies and actions
</LI>
<LI>
Tell stories about their neighborhood
</LI>
</UL>
There are no prerequisites to the course, but it will be helpful to know how to perform basic tasks in a spreadsheet, including sorting a table based on the values in a column, and adding new columns to a spreadsheet. It helps to have access to a laptop for two of the four classes, and a limited number of computers will be available if you don’t have one.
All classes will be held at the Hazelwood Branch of the Carnegie Library of Pittsburgh. Classes will be held according to the following schedule:
<UL>
<LI>
Wednesday June 28th from 2-4 pm: Conducting neighborhood property data surveys
</LI>
<LI>
Wednesday July 12th from 2-4 pm: Creating neighborhood statistics from property data
</LI>
<LI>
Wednesday July 26th from 2-4 pm: An Introduction to geographic information from the Data 101 series
</LI>
<LI>
Wednesday August 9th from 2-4 pm: Making online property maps in Carto.
</LI>
</UL>
* Optional work sessions may be held between classes based on need.
Learning Circles are a way for people to come together in an environment that allows you to ask questions and discuss with fellow learners. Participants come together to learn through lectures and tutorials, and then are led by a facilitator in discussion and activities. Learning Circles combine the best of self-directed and in-person learning.
 Space is very limited. Please register and the course facilitator will contact you with additional information, including reading assignments and details on what to bring to the first class.

Carnegie Library of Pittsburgh - Hazelwood

Our {communityGuidelinesLink} describe the sort of content we prohibit on Eventbrite. If you suspect an event may be in violation, you can report it to us so we can investigate.

To report other categories of prohibited or illegal content, submit {link}

Property Data Learning Circle

More events from Western Pennsylvania Regional Data Center/Carnegie Library of Pittsburgh

Discover more events from Western Pennsylvania Regional Data Center/Carnegie Library of Pittsburgh, from Community to other experiences you might love.

Still looking for the right event?

Explore all events in Pittsburgh and filter by date, category, and more to find the perfect fit.

Property Data Learning Circle

More events from Western Pennsylvania Regional Data Center/Carnegie Library of Pittsburgh

Discover more events from Western Pennsylvania Regional Data Center/Carnegie Library of Pittsburgh, from Community to other experiences you might love.

You might also like...

Browse more events with different dates, prices, and formats to find your next great experience.

Still looking for the right event?

Explore all events in Pittsburgh and filter by date, category, and more to find the perfect fit.