SECTION E: CLOSING

1. What would motivate your agency to implement a comprehensive data business planning process for the DOT?

Alaska: Alaska DOT&PF motivations are

• The opportunity to establish an improved planning process as the department shifts to a new data collection, storage, and reporting regime.

Full Text of State Questionnaire Responses 99 • Increased capabilities for spatial delivery of crash data to support the HSIP and SHSP.

Idaho: Capturing the true economic cost of crashes is a high priority as this would better aid in

the business of programing highway safety projects in the HSIP with a better economic model and B/C analysis.

Iowa: Iowa DOT is on that path now.

Maryland: A comprehensive data business planning process is a step in the development of a

diverse data-driven decision-support process throughout the DOT. DOTs are inherently data rich organizations, but much of the data is not integrated and treated like the valuable asset that it is in many DOTs.

Michigan: Michigan DOT has established a Data Governance Council that is still getting its

feet under it. This will cover all data.

Montana: The EA project that is just underway will have a data governance component and

data management strategy.

Rhode Island: The results of the pilot project for Local–State Data Integration for Asset

Management and Safety Analysis should motivate Rhode Island DOT to implement a comprehensive data business planning process in regards to safety data and governance.

Washington State: Washington State DOT’s motivations are:

• Directive from the Secretary of Transportation.

• Heightened level of awareness of problems and opportunities.

• Clear understanding of the distinctions between data (content) and technology (tools that enable collection, storage and use of content). Currently, technology is often viewed as the solution when Washington State DOT really needs more clarity about the business need or curation of the content.

• The appointment of a lead office with specific responsibility, oversight role, and ability to enforce necessary data policies;

• A data governance group with the responsibility for oversight at a high level, but not just from a policy perspective.

• Demonstration projects (scaled appropriately) to demonstrate the value of analysis in support of the decision-making process and to overcome concerns.

• Financial support across the business units (shared financial responsibility) for data management and integration necessary to operate and maintain the state route system cost- effectively.

2. What safety-related business process areas would benefit the most? Alaska: The following areas would benefit the most:

• Spatial analysis;

• Positive feedback to law enforcement agencies; and

• Integration with other program areas, including transportation asset management, highway design, health, and road weather.

Idaho: The creation of a data warehouse is a priority so records among the agencies can be

linked to obtain a comprehensive picture of the impact of traffic crashes in Idaho.

Iowa: Effective data planning would make it easier for everyone to use safety data such as the

media, legislature, cities, counties, enforcement, and department staff.

Maryland: The integration of safety and asset management data is one that would benefit

greatly.

Michigan: Michigan DOT suspects that benefits to safety will accrue based on how well the

department can establish and maintain many more engineering facts about the highway system. Michigan DOT will do this to improve the asset management processes, and this improved data will benefit the safety community. The biggest issues are the lack of monetary and staff support to determine MAP-21 proposed data requirements for all public roadways.

Ohio: There always has to be a benefit monetarily; however this is traditionally difficult to

lockdown. A major benefit is creating easy access to data where casual users can obtain the majority of answers.

Rhode Island: Asset Management–GIS would benefit the most as they will require additional

resources to effectively process and maintain the data.

3. What questions do you have for your peers regarding improving safety programs through data governance and data business planning?

Alaska: Alaska DOT&PF is interested in

• How agencies go about crash form spot checks, including:

– Sample size and whether the sample size is different for different crash severities, – Fields checked,

– Metrics,

– Feedback to crash processing team, and – Past performance.

• How agencies established an agency wide safety governance council? How does it function? What are the strengths and liabilities?

• Do any agencies have separate metadata and data catalogs?

Idaho: Obtaining information on successful design and implementation of data warehouses. Iowa: Do you have a web analysis tool? Did a consultant design and build that tool?

Full Text of State Questionnaire Responses 101

Maryland: SHA would like to hear about policies and practices from state DOTs on the

sharing of safety data.

Michigan:

• How can the safety community focus attention on as-built and maintenance processes to improve the quality of the engineering and roadway feature sets?

• To some degree safety analysis depends on the success of asset processes. How can the safety community make those decision makers successful?

• The MIRE FDE has been available for over 2 years. What have been the best practices of agencies to collect this information on all public roadways?

• What should be considered as a public road due to higher-volume private roadways that require signalization?

• What are some of the most successful automated data collection practices and processes along with the respective errors?

• How do you get local agencies to buy-in for collection of roadway data elements? • Have roadway data models been considered as part of the baseline data development until actual values are available?

• How can crowdsourced data be utilized?

• What is the future of data collection considering the potential for automated vehicles? • Should a hierarchy of data collection be established to address automated vehicle implementation? On what future platforms should data be collected and what for?

• Can the SHRP 2 Naturalistic Driving Study data be used to supplement currently unavailable datasets through the use of models and available characteristics in a roadway information database?

Ohio: Has there been any resistance with DPS supply citation data to the state DOTs? Rhode Island:

• How are other states organized to manage safety data and what was their process for making changes to their structure?

• What difficulties and successes have other states encountered with collecting– processing–governing safety data?

Washington State:

• What is the key to data integration?

• How does a transportation agency create awareness of problems and opportunities in data governance?

• How does a transportation agency advocate and gain support for analytics, data integration, and adherence to data management policies in such challenging times?

• How does a transportation agency move cost-effectively from mainframe systems and traditional data collection processes to more sustainable data systems, storage, and innovative data collection (such as lidar)?

• How does a transportation agency gain support for correct and consistent location referencing for any data collected on the state system?

• How do you articulate the business need for types of information at a resolution digestible within the time limits of an executive’s workload?

• How do you manage seamless adoption of new information technologies within your organization (such as roadway sensors, lidar, or open data architecture) while maintaining access to quality data during the transition?

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