Why a Housing Data Hub?

The Housing Data Hub was born out of a need to have a single place to learn:

  • What is the City of San Francisco doing about affordable housing?
  • What data is available about each of the policies and programs related to affordable housing?

While the City has a variety of affordable housing programs, they are implemented by several different departments or even governments outside of the City. By pulling all of these programs together in a single place, the Data Hub allows you to develop an understanding of the portfolio of housing programs in San Francisco.

And then there's the data. We wanted to enrich the content about the housing programs with their supporting data. We hope that readily available content, data and visuals spurs new thinking and approaches to affordable housing in the City.

A process of continuous improvement

Our philosophy is that it is better to release something sooner versus waiting for a perfect launch. That's what the "beta" designation marked by a ribbon in the corner implies. We are releasing our datasets in phases. Below we outline the three data phases and the current status of each dataset. This dashboard was inspired by gov.uk/transformation.

Even after data automation, the final data phase, we will continuously improve and add new visuals based on user feedback and common questions.

Discovery

1

We explore the dataset in partnership with the department and identify the most important visuals to showcase on the Hub.

Visualization

9

Dataset visualizations are posted on the Hub with supporting content.

Automation

2

Datasets are posted on SF OpenData, our open data portal, and are updated at defined intervals. A dataset is not complete until the Automation Phase.

Datasets in Discovery

  1. Inclusionary Housing: Office of Community Investment and Infrastructure units

Datasets in Visualization

  1. Homebuyer Assistance: Downpayment Assistance Loans Program
  2. Affordable Housing Finance: Affordable Housing Asset Management Database
  3. Affordable Housing Finance: Affordable Housing Production Pipeline
  4. Homeowner Assistance: Lead Grants Database
  5. Homeowner Assistance: Single Family Rehab Database
  6. Preference Programs: Certificate of Preference Program
  7. Preference Programs: Ellis Act Housing Preference Program
  8. Rent Control: Petitions
  9. Housing Overview: Housing Pipeline Data

Datasets in Automation

  1. Rent Control: Eviction Notices
  2. Inclusionary Housing: Pipeline and Completion Data

Acknowledgements

This project is the result of the contribution of many individuals.

Volunteers

The first working version of this website came from the National Day of Civic Hacking. Thanks go to both the San Francisco Brigade and Code for America for hosting us during this 2 day event. Our hackathon team was amazing! Victoria Ngo and Manu Koenig took the initial concept, simple though it was, and came up with something beautiful. Debbie Lefkowitz and another volunteer whose name has been lost helped structure and review the content. Raymond Lai was instrumental in hunting down various census datasets. Lastly, Nick Hong stitched together the pieces into a working backend and Kevin Lee helped create the initial visualizations. And these last two, both of Bayes Impact, stayed on and steadily attended SFBrigade hack nights to push us to a working prototype and functioning backend. We cannot thank you enough!

Over the summer, other volunteers dropped in to contribute. Thanks to Zoe Blumenfield and Krista Canellakis for their help on branding and finding a name! And Niaz Souti helped to not only read the content and remove jargon, but also drafted additional content for the Hub. Lamar Jordan provided incredibly useful contributions on web accessibility and Becca Bruggman helped us debug some code.

City staff and leadership

This project would not have been possible without the expertise and knowledge of the staff who actually manage and operate the housing programs in the city.

The staff in the many departments below were generous in both their time and effort. Many thanks to each of them for their help collecting and editing content as well as providing and patiently explaining their data. Thank you everyone!

The Mayor’s Office of Housing and Community Development. Kate Hartley, Chandra Egan, Maria Benjamin, Sonia McDaniel, Sophie Hayward, Brooke Barber, Vanessa Doyle, Lisa Motoyama, Sonia Delgado-Schaumberg, Mike McLoone, Teresa Yanga, and Benjamin McCloskey.

Rent Board. Robert Collins (thank you!) and the Rent Board contractors Brent Nelson and Mike Atwood.

Planning. The Information and Analysis Group produces the tremendous data resource tracking the housing pipeline.

Technology. Jeff Johnson and Samuel Valdez are helping with data automation and publishing the data on SF OpenData.

Other City staff contributed with their wisdom, guidance and occasional quick tips! Thank you Sarah Dennis-Phillips, Tomiquia Moss, Jeff Buckley, Kate Conner, Rebecca Foster, Kate Howard, and Chris Simi.

Open source community

This project is built on some incredible open source tools and inspirations that made our job a whole lot easier:

  • Jekyll is our static site compiler of choice. It has served us well and it allows us to host the Housing Data Hub on a gh-pages branch in GitHub to boot.
  • jQuery is a well-supported library for manipulating the DOM and doing other neat tricks with Javascript with a little less code.
  • Bootstrap 3 provides all the scaffolding and UI basics to get us going quickly.
  • C3 is a wonderful library built around D3 that gives us power without complexity including beautiful easy to configure, reusable charts.
  • Dave Guarino's lovely easy-choropleth project was the inspiration for the pattern we took with our choropleth mapping, but instead of Google Sheets we use trusty, reliable CSVs to power the map data.
  • Colorbrewer2.org provides a tiny javascript library that lets us quickly configure Color Brewer based ramps in code, which is very helpful for choropleth maps.
  • Mapbox.js is a Leaflet-based library that let's us connect quickly to our Mapbox basemaps and put data on a map.
  • Leaflet Omnivore chews on CSVs and spits out mappable layers for Leaflet
  • Leaflet fullscreen enables a map to go full screen so you can look at all that delicious data without distractions.
  • Prose provides us with a nice framework for allowing humans to actually edit content and plays nicely with Jekyll.

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