Hidden Gems: Finding Value in Open Data
We’ve all seen the movies, but technology taking over cities is happening in the real world too! As more devices and technology become connected throughout urban areas, cities are generating more data sources. Much of this information is posted on Open Data Portals where anyone can access, download, and use it for whatever purposes they may have. Unfortunately, cities are often not taking advantage of all this data they are creating, but with the right tools and the right motivation that can change. The curbside is one such incentive, with curbside management and digital inventories in increasing demand. Because of this, cities are looking at a variety of ways to collect this information without realizing they may already have the data they need (don’t worry, CurbIQ’s Curb Converter processes can still help you out if you don’t). This article reviews three types of datasets that can be used to create a digital curbside inventory: transportation asset data, real-time occupancy data, and signage data.
The first dataset category that should not be overlooked is transportation asset data. This can come in all forms – fire hydrant locations, transit stops, on-street bike storage, parking meters or even food trucks. Although this information doesn’t directly tell you what is happening at the curbside, it can often be inferred. There is no stopping in front of fire hydrants, a parking meter represents a parking space, a transit stop represents a no standing transit zone, the list goes on. By representing these assets as curb segments, a city can start to fill in their curbside inventory. There are several tools to convert this data, such as Curb Converter’s Open Data Automation processes, that can standardize and make the data user friendly. The gaps in the data can then be filled via surveying using Curb Converter processes or through the Curb Manager tool. An example of this can be seen below.
This is not just limited to asset data. Linear assets like bicycle or transit priority lanes translate to no stopping zones that can also contribute to the digital curb inventory.
Another data source that many cities have, but don’t often use, is parking occupancy data. Several cities have installed these sensors in on-street parking spaces and provide the data via an open API. Not only do these sensors inform where there are parking spaces at the curbside, but the corresponding occupancy data can also help inform curbside management decisions such as whether to expand parking or raise rates based on demand.
The final type of dataset, and arguably the best data for completing a curbside inventory, is curbside signage data. Unlike other assets, street signs can be related to create regulation segments; each sign represents the start, middle, end, or singular location of a regulation. Given enough info of what is on the sign such as directional arrows and time spans, a city has all the information they need to generate a complete curb layer.
As valuable as these datasets are, the content available is often messy and difficult to wrangle, manipulate, and generate a final output. We have all heard the saying before – garbage data in, garbage data out. Fortunately, the CurbIQ team has dealt with these issues before and developed solutions as part of the Curb Converter processes to help cities generate curb inventories from open data. We recently worked through this process with the Seattle Department of Transportation (SDOT) Curbside Management Team. They have lots of valuable datasets, including street signs, block faces, and a variety of assets, but had not yet pieced all the information together to generate a finalized curb inventory. The CurbIQ team manipulated this data using our Curb Converter processes to generate a complete curb inventory for the Belltown area.
As evident from the above screenshot of Curb Viewer, street sign data was used to populate the relevant information and geometries required for visualization. Additionally, asset data such as pay stations and bus stops was used to fill in gaps in the curb and additional curbside properties like parking rates and durations. As a result, our Curb Converter process was able to take several different data sources with unique attributes to a complete curbside inventory with all relevant information in a centralized location. This data for the Belltown area was also uploaded to the CurbIQ platform so that SDOT could try out our suite of tools. With CurbIQ, this data can be used internally for better curbside management as well as externally via an API to help mobility companies navigate the curbside.
As the example with Seattle highlights, cities often have some or all the components they need to create a curbside inventory, they just need someone to sort through all the data to generate it. Whether it be asset, real-time, or street sign data, our team at CurbIQ has the tools and processes to help cities take the first step in making the most of the curbside by creating a digitized curbside inventory. Please reach out for a free overview of your existing datasets, oftentimes the data is very similar to something we have seen before and we can work with you to generate a solution. With cities generating more information than ever, now is the time to take advantage and modernize the curbside.
Recommended for you
Park(ing) Day Could Be Every Day
Every third Friday of September, people across the world temporarily repurpose selected street parking spaces and convert them to small parks as part of PARK(ing) Day.
Curb Lanes Should Be A Public Good: How Publicly-Collected Open Data Can Make That A Reality
Google and TriMet created the first-ever open-source transit dataset in 2005. Since then, hundreds of transit agencies worldwide have released open-source GTFS feeds.
How CurbIQ helped IBI Group with CaféTO
The restaurant industry has been devastated by the COVID-19 pandemic. Those remaining in business have had to adapt their model and find creative ways to operate.