A couple of all-star technical entrepreneurs, Michael Schnuerle and Eric Roland, put together a fantastic app called “SafetyCheck” during this year’s Code for America Hack-a-thon. They won first place in the competition and launched their app for purchase in the iPhone App Store.
This app pulls in updated crime data and runs an algorithm to determine the safety rating of the exact location where the app is being used. Push notifications can be activated to alert you proactively when entering an area with a high score, indicating a large amount of crime. The algorithm takes into consideration the type of crime to weigh more serious offenses heavier. Future updates will account for population density to further refine the rating system.
Michael and Eric have demonstrated how simple tools can be developed to provide insight into the world around us with information that has been difficult to obtain in the past. Michael has been a strong advocate of the Open Data initiatives that are permeating local, state, and federal government agencies. The value of having access to this information may not be immediately obvious, but seeing simple apps like this give us a glimpse into the future use cases of this information.
We still have a long way to go before government information is readily accessible in a machine-readable format. Manual tasks are frequently part of the process today. These manual processes usually involve exporting data from an internal system and then uploading it into another format that is used in applications. Unfortunately this reality is slowing innovation because it limits the scalability of business models that rely on access to this information, especially if it is needed in real time or accessed nationally.
So much of the value in government information is stored at the local level, from individual property records to crime reports to tax liens. Getting this information from the local entities is where the “rubber meets the road” when building applications that rely on it. Before major innovation can happen with products and services that use this data, new tools will need to be created to get data out of local systems more efficiently with fewer manual steps.