Synopsis: States often have a vast amount of roadway data to manage and account for. Especially with the upcoming Model Inventory of Roadway Elements (MIRE), states need to be able to accurately collect and record their roadway data. This process is difficult, involving huge amounts of data and numerous local and state agencies working together. Even when data is collected, maintaining the data and relationships with local actors provide on-going challenges.

AppGeo is helping states modernize their roadway data. This webinar (recorded on June 10th, 2021) brings together Peter Lemack, GIS Consultant at AppGeo, Patrick Whiteford, Geographic Information Systems Manager at the Arizona Department of Transportation, Ryan Blum, Manager of Geospatial Data operations at Works Consulting, and Caitlin Schneider, Senior GIS analyst from AppGeo to discuss the challenges and solutions that come with updating and maintaining roadway characteristic data.             

The Road Less Traveled

Whiteford: Before starting this project I was thinking, ‘okay let’s see…we collect all of this data, but how do we maintain it for the long term?’ That’s where AppGeo, and Works Consulting came in and helped identify tools, and also functionality to help us fill in the blanks related to these things so that way we could build something once and use it. 

One of the most interesting is that all the state agencies that I work with have very similar reporting requirements, but we all get there from very different places. I wanted to create a standard here with data as the backbone to support our reporting requirements. To create that standard, we needed to develop local reporting so the data could be up-to-date long term.”

While states often collect large amounts of quality data, getting access to that data is often more difficult than it needs to be. Additionally, data collection efforts are hamstrung by limited governance, making it difficult to coordinate stakeholders. As a result, state data is often managed in inconsistent ways, harming the efficiency and ease of use for consumers. These issues can lead to duplications of effort and long periods of downtime as actors wait for data to become available or properly formatted for use. 

To solve these problems, the Arizona DOT focused on identifying local stakeholders and specific areas in need of data collection. ADOT then teamed up with AppGeo to create a long term plan to maintain these data governance systems. By building a forward facing sustainable data program, AppGeo helped ensure that ADOT’s investment in data collection would be effective for years to come. 

Walking the Road

Schneider: “ADOT was already doing a lot of things really well. But I think there is a lot of value to coming in with a fresh set of eyes and an unbiased view. We also kept in mind suggestions from the HPMS reassessment. AppGeo’s team then developed a strong set of recommendations that could then be evaluated and then incorporated as the project progressed.”

When AppGeo came to help ADOT, the focus was on creating a sustainable data management system. To do that AppGeo added more features that facilitate communication between workers on the project, such as confidence indicators, comment sections, and analyst trackers for certain tasks. 

One of the hardest parts of the project was to review the documentation and methodologies being used at ADOT. As new scenarios and events occur, it is key to write down the protocols required to address them for easier future use. By continually updating and improving ADOT’s methodology throughout the project, AppGeo was able to build a useful resource that could help standardize data management for use for years to come.

How Safe is it?

Blum: “As a team we decided the way to look at how best to achieve compliance was to look at the gaps. We did gap analysis to find the existing gaps within the data that we already had, schema gaps, and collection standard gaps… We looked at those data gaps in three different tiers. We delivered our findings to ADOT and gave them a recommendation report to help them do better in the future. We also gave them updated schema and extraction workflows, to help them best update their existing work. Finally, we did an FDE gap analysis script, to determine what was missing at any time throughout the project.”

To be compliant with MIRE (Model Inventory of Roadway Elements) ADOT first had to evaluate how their data matched up with federal standards. AppGeo created a script that could be run at any point during the project, to specifically tell ADOT what gaps exist between for each of those data items, as well as where those data items are and what attribution they require. This system helped to keep ADOT on track and keep them specifically aware of what further changes are required, as well as their overall progress towards total network coverage. 

Does the Sun Really Set in Arizona?

Whiteford: “We’ve had huge accomplishments in relation to this project. So far we have collected over 9,000 miles of roadway. Additionally, the fourth phase of the project is going to be started in the upcoming months. We will continue to create data to meet MIRE requirements, all the way down to local roadways to fill in gaps as much as possible.” 

With the ADOT system headed towards sustainability, the possibilities for roadway data are endless. However, to maintain this system it is key to have continued communication with local partners and  develop departmental relationships that will ensure quality data exchange long into the future. By focusing on improving the data provided through better management, ADOT has been better able to do data visualization and make meaningful long term decisions. 

Continued reading: Roadway Characteristics – Data Extraction, Validation, and Ongoing Maintenance