2016 marks five years since I decided to spend all my time thinking about how we finance the places people live, work and play. I started by exploring new donation-based models for public goods and am now working with Neighborly on the much more established (but less widely understood) public finance market.
Whichever model we choose to finance community development or the organizations that make it possible, there's one factor that can make or break our efforts. High quality open data.
There's no need for me to spend much time here making the case for open data. Plenty of other folks have done massive, incredible work in this area. Most people understand that solving basic information asymmetries is a step forward. That doesn't mean participants in a competitive system can't collect data and gain an advantage from those insights, but rather it means that fundamental information about the system and its workings should be open to any and all participants who want it. Especially when the system is funded by tax dollars.
But sometimes it's not clear exactly what 'open' means, or should mean. How opaque is too opaque? The answer to all of these questions is highly context specific.
This past week Amanda Roberts of the Federal Reserve's Community Development Group and I published a working paper that tries to tackle these questions in the context of how donation-based crowdfunding is being used for community development. It's called Understanding the Crowd, Following the Community: The Need for Better Data in Community Development Crowdfunding. We suggest some practical data transparency measures that crowdfunding platforms can take that would enable a broader range of actors (e.g. foundations, community development organizations, quasi-governmental organizations) to support crowdfunding. Our goal was to answer the question 'how open do we need to be?' in a way that will expand the number of potential opportunities for impactful projects and increase public trust in the system and encourage meaningful competition between platforms. I'd love to hear what you think.
Although I moved on from focusing on donation-based crowdfunding over a year ago by deciding to join Neighborly, I've been excited to see how interest in this area has continued to grow and attract the attention of new audiences.
Meanwhile, many of the issues I explored in crowdfunding data are directly relevant to the public finance work we're doing at Neighborly.
Collecting public finance data that is in theory public isn't easy or free. Analyzing and verifying it isn't either. It can be both difficult and expensive. There are also fundamental pieces of information that public finance relies on that are proprietary, and therefore neither easy nor free to access. What that means is that public agencies like school districts are directly or indirectly paying more to build schools.
So we've been building tools to start addressing these issues, and last week we began releasing those tools to the public finance community. We're working closely with the individuals who spend every day working with this data on behalf of public agencies to figure out how to get public data to them as easily as possible, for free. Because public data should always be free.
If you're based in the San Francisco Bay Area and would like to take a deeper dive into what we're working on or chat about data issues you've faced, drop into General Assembly on January 12. I'm giving a talk about our work at the coalface of public finance data, and suggesting some ideas about how we can build self-reinforcing data communities that support access and improve data quality for all. It would be great to see you there.