This story was originally published by Data-Smart City Solutions.
Pittsburgh's Burgh’s Eye View is represented by this adorable little bird looking through a magnifying glass, and is our central one stop shop from the public perspective for our open data.
Almost all of our point-based open data from our regional open data website has been converted into a web map. The slide that we're looking at now shows you what it looks like in its current form. As I'll describe going further, this has been a very iterative process for us, but this is sort of a snapshot in time.
What you can see here is we started with a lot of the 311 requests, but we're actually pulling a variety of public safety data, capital projects, and asset data as well as, of course, the 311 and relevant building information data. On this side is a list of all the different sorts of points that we're pulling directly from open data onto the Burgh’s Eye View application.
For us this has been a very sort of customer- and client-based project where, as I'll describe in a minute, we started building something like this for the police, but have actually built it out for a variety of other communities. And so the user experience has been very important to us and we have focused on mobile first for the way that we designed the interactive map. While it works on the desktop for doing heavy analysis, it's also really easy to use on a phone or tablet for more operational work. And we have a large number of our departments who are now using different aspects of it in their work, mostly in the field on those mobile applications.
Toward that end, in this picture I have my team, a portion of the folks who built this application, along with Mayor Peduto in the middle here. What you see along the sides are some of the many versions of the bird, which have evolved over the last 18 months to two years. The original bird is just the bird with the magnifying glass. But over the last 18 months, as we have designed these for specific departments and offices, we have built each a version of the bird with a different hat or wig, in the case of the barrister's wig on the city council bird.
When we pitched this webinar, we talked a good bit about platform and I think that Tom, Lillian, and I today each represent projects that have a lot of similarities, but also a lot of operational and application development differences. A big one of those is that we’re each on different platforms.
Our application is built entirely in R Studio. And this is a list of the packages that our team has used to develop this.
I include this to just let folks know that if you have any sort of experience with R or R Studio, it has been a fabulous tool for us. For us it also really represents what I consider to be a big, big change in the way government technology functions. In that, instead of having us build really specific bespoke applications for each of our departments, we've been able to be iterative and user-focused and build up the applications based on our central project that best meet their needs.
You can see that we have a lot of public policy degrees here. To fill this, we didn't necessarily need a lot of deep engineering skills in application development. It's been much more of a process of understanding things from the policy angle and facilitating the interaction with the data from city workers and helping to build something that they can understand just using the R Studio platform.
This of course has been a revolution for us in the city of Pittsburgh. We're very much a financially constrained municipality, and so the fact that we still, ourselves, are using open-source software, has been really significant and I don't think this project would have happened otherwise.
This project started with a request from our former police chief. He was a really great leader and somebody that our team really looked up to. But one of the things that he realized when he came into his position as the police chief in Pittsburgh was that the department really had a distinct and significant lack of access to their own data. There were no resources available, financially or otherwise to really remedy that, at the time. So what my team was able to do was to take all these different data sources, which you can see from this list is sort of quite the hodgepodge of information.
We are pulling from sources from systems that are hosted here on site by Oracle. We are pulling from web APIs for SaaS [Software as a Service] applications that we have, as well as directly from spreadsheets that live on people’s desktops. I know we are speaking to a government audience here that has knowledge of that phenomenon.
So what we were able to do is develop custom pulls that pull every hour from these different systems, so that we can build this little map. So this is the beginning of it and how it first looked when we built it for them. You can see we have the cute little police bird in the corner with his handcuffs.
So we rolled this out in the different police divisions and we were able to get a lot of feedback, and over time we were able to change it to better reflect the information and data needs of the police officers themselves. So we were able to pull in from different systems, set it to default to various categories and new sorting options such as whether or not a case was flagged as a domestic incident, as well as group the incidents directly by what shift they happened on, which was something that the police commanders requested.
This also had a big impact for us because once we got started building this map, we then had access coming from the police systems. So we were able to use that to build other sorts of business intelligence tools, eventually building it out to a whole suite of data tools that can be used by the division commanders on down.
In thinking about how offices like ours can relate to program offices, this process has been a really fabulous way for us to develop relationships with those folks. The process of building the police something as easy to access and understand as a web map has just been a really great way for us to sort of do some culture change and help them to understand that we're really there to help them and to think about data more strategically.
A lot of what we talk about in the Civic Analytics Network is some of the more scientifically and statistically exciting predictive work that the different cities are doing. Through the Burgh’s Eye View development process we were also able to move from the realm of descriptive statistics into predictive.
I know that there's probably a whole state of opinions about hot spot policing out there, but our leadership has said that this is something that they wanted to try. Through this application we were able to partner with Carnegie Mellon in order to do hot spot predictions. And so we now have our division commanders sending our police officers into these zones to spend extra time there every day.
So as this project continues, we'll be anxiously looking forward to see differences in the outcomes of crimes occurred.
We took our team out on the road for the public-facing version in 32 different community meetings in February and March of last year and this year. Through that we were able to get a ton of feedback about how people are using the application, how different community groups and block watches are interested in new data coming from the application, and that has really helped us to build our road map for the public facing version of the application.
So we are excited that next week we're going to launch a new parcel map, which is mostly developed from our department of finance and includes a lot of tax and ownership data that has not been in the same place before. And then, moving forward we are looking to incorporate ourselves better with our zoning and planning departments, so that we can give community residents a way to look at any upcoming changes or hearings that might be taking place in their neighborhoods, because those were things that we heard at the meetings.
For us, this platform has just been a really fabulous way for us to allow people access to all the data that we've been so hard at work gathering over the last three years. The fact that we built it ourselves in R Studio and have the ability to make pretty quick alterations and form new versions of it for new audiences has really allowed us to take full advantage of using all of this data and bringing it to people's attention in a sort of friendly, understandable way.