Thoughts on the Potential of Open Data in Cities

The promise of Open Data has drawn most major US cities to implement some sort of program making city data available online and easily accessible to the general public. Citizen hackers, activists, news media, researchers, and more have all made use of the data in novel ways. However, these uses have largely been more information-based than action-based, and there remains work to be done in using Open Data to drive decisions in government and policy-making at all levels, from local to federal. Below I present some of the challenges and and opportunities available in making use of Open Data in more meaningful ways.


Standardization and Organization

Open Data is dirty data. There is no set standard between different cities for how data should be formatted, and even similar datasets within a city are often not interoperable. Departments at all levels of government often act independently in publishing their data, so even if most datasets are available from the same repository (e.g. Socrata), their organization and quality can differ significantly. Without a cohesive set of standards between cities, it is difficult to adopt applications built for one city to others.


The way data is uploaded and made accessible must be improved. Datasets are often frozen and uploaded in bulk, so that when someone downloads a dataset, they download it for a particular period in time, and if they want newer data, they must either wait until it is released or find the bulk download for the newer data. This involves more human effort both in the process of uploading the data and in downloading and processing that data. Instead, new data should be made immediately accessible as a stream with old data going back as far in time as it is available. This allows someone to access exactly as much data as they need without the hassle of combing through multiple datasets, and it removes the curators need to constantly compile and update newer datasets.


Compared to the amount of data that the government stores, very little of it is digital and very little of what is digital is publicly available. The filing cabinet should not be a part of the government storage media. Making all data digital from the start makes it simpler to analyze and release. Finally, much of the data the government releases is in awkward formats such as XLSX and PDF that are not easily machine-readable. If the data is not readily available and easily accessible, it in effect does not exist.


Most of the publicly accessible records that the government has are not readily available unless FOILed. The transparency argument of Open Data could be taken to a completely new level of depth and thoroughness if information at all levels of government was made readily available digitally as immediately as it was generated. Law enforcement records, public meetings, political records, judicial records, finance records, and any other operation of government that can be publicly audited by its people should be digitally available to the public from the moment it is entered into a government system.

Private Sector Data

Companies such as Uber and Airbnb have come to collect immense amounts of data on transportation and real estate that have historically fallen under regulated jurisdiction. Decisions should be reached with private companies to allow governments to access as much data as is necessary to ensure proper regulation of these utilities. This data should in turn be added to the public record along with official government data on these utilities.


Analytic Technologies

Policy-making should be actively informed by the nature of a constituency. Data-driven decision making is much hyped, but making it a reality requires software that easily and quickly gives decision-makers the information they need. From the city to the federal level, governments should have dashboards that summarize information on all aspects of citizens’ lives. These dashboards can contain information about traffic, pollution, crime, utilities, health, finance, education, and more. Lots of this data already exists within governments, and surely there exist some dashboards that analyze and visualize these properties individually, but to combine all available data on the population of a city can give significantly more insight into a decision than any one of these datasets alone.

Predictive Technologies

Governments have data going far back into history. Cities like New York have logged every service request for years, and that data is readily available digitally. Using the right statistical analysis on periodic data like heating requests, cities can start to predict which buildings might be at risk for heating violations in the winter, and can address such issues before they happen. The same can be applied to pot holes, graffiti, pollution issues and essentially any city-wide phenomena that might occur regularly. More precise preventative measures can be taken with more confidence, and eventually, the 311 call itself can be ruled out entirely.

Future Outlook

These ideas have the potential to radically change the way we engage with our cities and our politics. We can make decisions based unambiguously on what is happening in the world, and we can refine those decisions based on measured changes in the world over time. A population can know exactly if its citizens are getting healthier, safer, and smarter, and how to aid in these pursuits. Areas of governance that need more attention and potential approaches will become increasingly obvious as more information is combined and analyzed in meaningful ways. Decisions and their outcomes can be made with more confidence based on a more rigorous process. By making the most of Open Data, we can go beyond interesting information and begin to drive political action that directly benefits our cities, states, and nation.

A Note on Privacy

All of the ideas presented above have serious implications for the privacy of individuals and populations. These ideas have only considered the best-case uses of data in our society. Whether a government is analyzing granular data or data on a population in bulk, care must be taken to respect the privacy of its citizens. There is ongoing dialogue about how to balance data collection and privacy, and it is essential that governments and citizens take part in this dialogue as new technologies are developed and our societies become more data-driven.

Reinvent 311 Mobile Content Challenge: Homeless Helper NYC

NYC 311, with help from Stack Exchange, held the Reinvent 311 Mobile Content Challenge, which called on developers to use NYC’s revamped Open 311 Inquiry API to make city information more readily available on people’s mobile devices.

I started out focused on education data, but it was messy and too loosely organized to be of any immediate use. If you want to extract meaningful information from it, you could, but it would take some cleaning up and organizing to make useful. It isn’t as easy as displaying an API call from a mobile device.

After looking through more of the available data and consider the different use cases, I settled on an app designed to help homeless people in the city. This seemed like a terrible idea at first — how do you use technology to help those without access to it?

A few ideas came to mind. A map of food banks and soup kitchens (along with directions) could be useful. There were also lists of intake shelters online, but no coherent sets of shelters, so a map of shelters would also be useful. Finally, there were also information-based services that the city offered — information on food stamps, homeless prevention, youth counseling, job services, and other outreach information. Putting all of this data together wouldn’t be terribly difficult, and it would create an app that someone might find helpful. Homeless people typically don’t have access to smartphones, but outreach groups like Coalition for the Homeless could use technology to help those without it.

The app is modeled after the data from the API, with different objects for each type of API response. This allowed me to easily create maps give any set of facilities (shelters, food banks, etc.), and information pages given any city service. In this sense, the Open Inquiry API’s design has allowed for flexibility in adapting the app to easily include more data.

One of the main strengths of the Open 311 API is that once an app is created for one city, it should be seamlessly compatible with data from another city, since the API calls are all the same — all that changes is the city that serves up the data. This is a fantastic ideal outcome, but the implementation is slightly off, especially in this particular use case. The data I used needed minor refinements — nothing extreme, but I had to manually decide which services were relevant to this audience, since there is no “homeless” category. I also whipped up some quick Python scripts to add more useful latitude/longitude data from street addresses using the Google Maps Geocoding API.

Perhaps the biggest flaw in the data is the lack of information in API calls. One of the goals outlined by the people at NYC 311 was to reduce the number of calls to 311 asking for information that was readily available online. A mobile app is a great way to make this information more immediately available, but for most services, nothing more than a description was offered. The “More Information” and “FAQs” sections simply said “Call 311 for…” — the data isn’t useful if it simply redirects to the old method of calling for information.

Besides the lack of completeness and consistency in the city’s data, the potential for interesting tools and visualizations is clear. There’s a ton of data, the challenge is in sifting through it and making it easily usable.

The demo event itself was fantastic fun. The other contestants had impressive applications, most of which focused on low-income resources and real estate data. I met Joel Spolsky, who offered some sharp and honest advice for the contestants (think StackOverflow, but in person), Noel Hidalgo, who runs BetaNYC as a part of Code for America (check out their projects here), the talented people of StackExchange, designers from HUGE, and a gaggle of kind people from NYC 311. In the end, Homeless Helper NYC won a prize for “Best presentation of 311 information targeting a specific audience,” and it’s out now on the Play Store. You can also contribute to the source code on GitHub!