Property Data User Meeting Recap, January 2018

by Bob Gradeck

February 7, 2018

We were joined by over 35 people for our third property data user group meeting on the morning of January 25th at the East Liberty Carnegie Library. These meetings provide us both with an opportunity to share our progress, but they also enable us to hear what our users are looking for when it comes to using property and housing data. For the first time, we also took advantage of an opportunity to user-test one of our newest data tools. For more on what we did at our first and second meetings, please see our previous blog posts (meeting 1, meeting 2). For more on what we do at these meetings, the Sunlight Foundation collaborated with us to develop a playbook for Data User Group meetings and included it in their very first installment of the Tactical Data Engagement Playbook series.

This time, we used “mentimeter” software enabling us to capture participant feedback during the session. Participants were able to use their smartphones or computers to respond to questions posed by us throughout the meeting. We also threw in a few open data trivia questions and other oddball prompts to keep it fun. We are now asking participants in the meeting to answer a few follow-up questions for us, and we’ll add their responses to this blog post in a few weeks. If you didn’t attend the meeting, you can take the survey, too. There are a few fun trivia questions included.

Inspired by the team behind Data Rescue, we also shared “data storybooks” designed to capture our users’ data stories. If you have a story and want us to send you a storybook, just let us know.

One of our attendees shared a data story with us using our new data storybooks

Progress Update

The agenda for the meeting started with a brief welcome and introductions, and then we moved right into our progress update (see the slides). In the update, we shared the following:

  • A listing of new data that were made available since the previous meeting, along with data in our road map that is not yet open.
  • Trainings developed in 2017 included an all-new Data 101 introduction to data literacy series, and a four-part learning circle for property data users.
  • A new version of the Regional Data Center Website was launched (see our blog post for more details).
  • New tools developed or substantially improved based on user input include our “parcels n’at” parcel data downloader, Burgh’s Eye View Parcels, and the Parcel Dashboard.
  • We didn’t make as much progress as we would have liked in developing new data user guides for property data. We’re sorry!
  • Data Day was also held in October, 2017, along with a series of other data events including Data Rescue and a social event for students.


Affordable housing conversation

At the end of the presentation, we showcased Housing Insights, a new affordable housing data tool developed in Washington, DC, and briefly discussed the state of local data to support affordable housing stakeholders. Those who worked to assemble affordable housing data in our community shared several of the following observations:

  • Data is siloed across multiple sources, including HUD, the Pennsylvania Housing Finance Agency, local housing authorities, housing developers/providers, and local redevelopment agencies;
  • Inconsistent terms were used to refer to properties, making it difficult to link data across agencies;
  • Housing tenants are generally unaware of the programs and regulations that may affect their housing situation;
  • Organizations doing the work did not share with one another, and were often trying to create a master housing database independently;
  • There is a need for data on available units, along with expiration dates on housing subsidies.

Participants at the meeting suggested that we at the Regional Data Center convene a follow-up meeting to dive into a deeper discussion of affordable housing data sources. We plan to do this. If you’re interested in attending, keep an eye on our events calendar, and be sure to sign up for our newsletter for more details. If you were in attendance at the meeting, we’ll let you know when it’s scheduled via email.


Soliciting ideas

We then moved into the main part of the meeting, where we asked participants to share their ideas for using data with us. We started by sharing one of our favorite prompts with participants, and asked them to record their ideas on paper in a solo activity.

Confession: We stole this prompt from our friends at the NYC Planning Labs

Once our attendees each completed a few prompts, we asked them to participate in a second activity designed to categorize ideas and spark small-group conversation. Participants joined with others seated nearby to form one of seven groups. We then gave each group a large sheet of paper containing the name of one of seven topics we wanted to use to organize their ideas. Here’s the list of topics:

  • Housing Development and Rehabilitation
  • Addressing blight and vacancy
  • Analyze community conditions/planning
  • Prevent displacement
  • Improve health, safety, and the environment
  • Enhance housing affordability and expand opportunity
  • Other

Once each group was given the paper, attendees collaboratively added their ideas for using data for the assigned topic on large paper. After a few minutes of recording ideas on their first sheet of paper, we then asked our attendees to pass their sheet to another table in a “pass around” activity. When each group received a new sheet for a new topic, we asked them to add any ideas that a previous group didn’t already list. This activity continued until each group recorded their ideas on each of the seven topics.

Re-enactment of the pass-around activity used to generate ideas for using data

We then collected each of these ideas, and are now sharing a curated list back with participants, asking them to vote on their favorite ones in a follow-up survey. The full list of ideas captured in this pass-around activity can be found on our roadmap document. We will share the results of the voting in this blog post once complete.


Property Owner Name Discussion

The fact that Allegheny County has an ordinance which prohibits property owner names from being shared in bulk open data downloads or in a searchable database has limited the impact users can have with the property assessment data. This data is not shared due to privacy concerns related to law enforcement officers and employees of the judicial system. Please refer to our assessment data user guide for more details.

After getting lots of questions from data users interested in analyzing property ownership in their neighborhood, we took a look for other communities that have developed procedures to sensitively handle names of law enforcement officers and court employees in assessment data while still releasing owner name data to the public. We recently spoke with Bonnie Hebert of the Harris Co. Appraisal District in Houston Texas to learn how they manage owner names in their system. Here’s what we learned:

  • In Texas, there is a statewide law enabling people (and some relatives) in specific occupations and victims of family violence to have their name removed from all property records that are maintained by the Appraisal District. These occupations are tied to law enforcement, the courts, armed forces, medical examiners, corrections and related functions. These categories are defined by the State of Texas, and listed on the Request for Confidentiality form. 
  • Outreach to people eligible is handled through the courts or law enforcement. A very limited number of staff at the appraisal district have access to these completed forms and are authorized to make the change within the appraisal district. When a parcel is transferred, the confidentiality status is removed.
  • Anyone regardless of occupation can also make a request to have their name removed from online property information. The names are removed from the web-accessible records only. The request to remove form is also on their Website.

The County asked us to collect suggestions of how attendees would like to use owner name data. The ideas shared at the meeting can be grouped into the following five main categories:

  • Link housing condition data to assessment data to hold sub-par landlords accountable;
  • Track housing market investor activity;
  • Contact property owners regarding community news and service delivery (home repair, health/safety inspections, legal assistance);
  • Acquire portfolios of a property owner as part of an affordable housing strategy;
  • Landlord engagement strategies (e.g. landlord focus group recruitment).


General Discussion

To close the meeting, we opened the floor for general comments and suggestions, and also asked participants to suggest future activities. Here were a few of the items shared in the conversation or in response to survey prompts:

  • We were encouraged to have follow-up meetings devoted to specific topics, including affordable housing data and data needs/issues of non-City municipalities.
  • Participants requested a wide variety of training, including training in use of the property dashboard, mapping and data visualization tools, data linking techniques, and use of API’s.
  • A few people also requested that we offer additional networking activities and do more to build learning communities.


User tests

Following the meeting, we asked a few volunteers to stay for lunch and test our latest iteration of the Property Dashboard. Staff and friends of the Regional Data Center helped to proctor these tests. We used the Civic User Test (CUT Group) model developed by the Smart Chicago Collaborative (recently renamed the City Tech Collaborative). We found the presentation by Sonja Marziano and Denise Linn Riedl at the fall NNIP Partner Meeting especially valuable, in that it helped us structure our user testing protocol around a few key tasks (you can see Sonja in action at this link). Their support also helped us understand the ways to communicate with our users in order to get the most value out of the tests. We will use the feedback to improve the property dashboard before we move the product out of its “beta” release.