MICHIGAN DEPARTMENT OF TRANSPORTATION

SAFETY DATA PROCESSES AND GOVERNANCE 

PRACTICES

CASE STUDY

FHWA-SA-15-059

Prepared for

Federal Highway Administration

Office of Safety

November 2015
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MICHIGAN DOT CASE STUDY

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Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation

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of the information contained in this document. 

The U.S. Government does not endorse products or manufacturers. Trademarks or 

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objective of the document.

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MICHIGAN DOT CASE STUDY

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ACKNOWLEDGEMENTS

The following individuals graciously provided information needed to develop this case study.

Name Title Department Email/Phone#

Ron Vibbert Chief Data Steward Michigan Department 

of Transportation 

VIBBERTR@michigan.gov

517-243-2754

Dean Kanitz Safety Data Analysis 

Engineer

Michigan Department 

of Transportation

KanitzD@michigan.gov

517-335-2855

Rob Surber Office Director of 

Department of 

Technology, 

Management and 

Budget (Enterprise 

Management 

Solutions)

Michigan Department 

of Technology, 

Management and 

Budget 

surberr@michigan.gov

517-335-2820
MICHIGAN DOT CASE STUDY

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ACRONYMS 

Acronym Description

AASHTO American Association of State Highway and Transportation Officials 

DOT Department of Transportation

FHWA Federal Highway Administration

GIS Geographic Information System 

IT Information Technology

LRS Linear Referencing System

MIRE Module Inventory of Roadway Elements

NCHRP National Cooperative Highway Research Program

MDOT Michigan Department of Transportation 

NCHRP National Cooperative Highway Research Program
MICHIGAN DOT CASE STUDY

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TABLE OF CONTENTS

INTRODUCTION..................................................................................... 5

DATA GOVERNANCE PRACTICES AT THE MICHIGAN 

DEPARTMENT OF TRANSPORTATION .............................................. 6

Policy............................................................................................................................ 6

Technical...................................................................................................................... 8

Michigan Safety Data Management Benefits ........................................................... 9

APPLICABILITY TO OTHER STATES.................................................10

RESOURCES...........................................................................................12

REFERENCES..........................................................................................13
MICHIGAN DOT CASE STUDY

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INTRODUCTION

The Michigan Department of Transportation (MDOT) is a leading State DOT in the 

implementation of formal data governance policies and practices. Benefits for States adopting 

data governance from a policy, practical and technical perspective are described in the National 

Cooperative Highway Research Program (NCHRP) Report 666: Target-Setting Methods and Data 

Management to Support Performance-Based Resource Allocation by Transportation Agencies (2010): 

From a policy standpoint, data governance promotes the understanding of data as a 

valuable asset to the organization and encourages the management of data from both a 

technical and business perspective.

On a practical level, the use of a data governance model provides for access to data 

standards, policies, and procedures on an enterprise basis. It provides a central focus 

for identifying and establishing rules for the collection, storage, and use of data in the 

organization.

From the technical perspective, use of data governance results in reducing the need to 

maintain duplicate data systems, improves data quality, and provides new opportunities 

to implement better tools for managing and integrating data.

The purpose of this case study is to summarize how the MDOT incorporates a data

governance structure into their standard business operations and how it has helped them to

improve their safety data systems and processes. “Data governance can be defined as the 

execution and enforcement of authority over the management of data assets and the 

performance of data functions” (NCHRP Report 666, 2010) and is an integral component used 

to facilitate management of data systems as part of an agency’s data business plan. 

In the case of MDOT, a set of data governance practices provides the foundation needed to 

develop a comprehensive Data Business Plan, to support MDOT’s Strategic Highway Safety Plan

Highway Safety Improvement Program, and improve information systems that manage data 

needed for safety analysis, planning, and decision-making. 
MICHIGAN DOT CASE STUDY

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DATA GOVERNANCE PRACTICES AT THE MICHIGAN 

DEPARTMENT OF TRANSPORTATION

The State of Michigan Governor’s office issued an Executive Directive in 2013 (Snyder, 2013) 

that substantially supports the data governance practices at MDOT and other state 

departments. This provides a top-down data governance structure that formalizes many years 

of data management practices in Michigan and helps the DOT continue to evolve their data 

governance framework. 

This case study explores MDOT’s data governance practices according to policy, practical and 

technical perspectives. 

Policy

MDOT began to implement policies targeting management of their data systems in the 1990’s 

as part of their asset management program. The goal of these policies was to establish 

methods and procedures to collect data once for multiple uses. Recently, there is a national

demand for quality data for planning, analysis, reporting, and decision-making. Because of this 

demand, many states are adopting strategies to better manage their data. This has resulted in an 

effort to collect data once and use it for multiple applications and has been formalized in several 

states through data improvement strategies and strategic plans. Michigan’s utilization of their 

data management practices has yielded a return on investment by eliminating duplicate data 

collection, which has reduced costs associated with maintaining the same data in multiple 

application systems. Policies regarding data management practices at Michigan DOT are 

supported by the office of Governor Snyder, Executive Directive No. 2013-1, Data and 

Information Sharing, Management and Governance. 

In response to Michigan’s Executive Directive (Snyder, 2013) the MDOT established: (1) a 

Data Governance Council, whose purpose is to implement data management within the 

Department (2) the role of Chief Data Steward, and (3) identified several data stewardship 

roles throughout the Department. Established roles that support data governance prepare 

states to launch a Data Business Plan that ensures quality data to support safety programs 

including the Strategic Highway Safety Plan and Highway Safety Improvement Program. 

MDOT uses a data governance model that includes oversight of the data management function 

by a Data Governance Council that meet monthly. Membership on the council includes 

representation from major business process areas, as well as representation from the 

Information Technology (IT) department. The Council developed a charter to better align their 

responsibilities with the direction of the Enterprise Information Management program 
MICHIGAN DOT CASE STUDY

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established by the governor (Snyder, 2013). They also help to establish policies for data 

governance and will participate in development of data dictionaries and metadata for all major 

systems and data sources. 

In addition to establishing a Data Governance Council, MDOT established a Chief Data 

Steward. The Chief Data Steward has two primary roles in data management. The first is to 

implement the statewide Enterprise Information Management within MDOT. The second is to 

chair the Data Governance Council. Although identification of all specific job duties remains to 

be completed, it is generally understood that the Chief Data Steward can and does have 

influence regarding the design of databases and determining how projects are developed. The 

Chief Data Steward also ensures the DOT’s and the State’s Enterprise Information Management 

efforts are mutually reinforcing. 

MDOT is establishing data stewardship models to identify governance ownership for specific 

data systems. Data stewards will ultimately be responsible for establishing and using business 

rules that govern data in each business area. Stewards for safety-related data systems, will be 

established in areas such as traffic, crash, and roadway inventory data.

MDOT’s current data management activities center on migrating and continuing to develop

their data dictionaries and metadata. Prior to the directive, the dictionary tools, that underlie 

capital programming and asset management process definitions, were obsolete. MDOT is

migrating these definitions and metadata into a single tool maintained by IT staff. Once 

migrated, the Department will review current data stewardship assignments, and expand these 

assignments to include systems not previously governed. Many of these are safety systems or 

management of data that support safety programs. 

Joint Application Development sessions in Michigan will likely be used to support the continued 

development of the dictionaries and glossaries, and help better define stewardship 

responsibilities. A common definition for Joint Application Development is: 

A development methodology system originally used to designing a computer-based 

system, but can be applied to any development process. It involves continuous 

interaction with the users and designers of the system in development. Joint Application 

Development utilize a workshop session that is structured and focused. Participants of 
MICHIGAN DOT CASE STUDY

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these sessions would typically include a facilitator, end users, developers, observers, 

mediators and experts.1

 

Development of similar business terms, dictionaries and business terms glossaries is 

recommended in NCHRP 666 as a method to support implementation of a data governance 

framework. 

Technical 

From a technical perspective, MDOT uses an integrated Linear Reference System (LRS) to 

maintain location data, as well as, an integrated web-based enterprise base map to disseminate 

data. New data collection tools, such as use of Light Detection and Ranging (LIDAR), are under 

investigation and will reinforce the policy of collecting data once and using it many times. 

MDOT is using AASHTOWare Safety AnalystTM and the Highway Safety Manual, in addition to 

GIS tools, to support analysis of safety-related data. A certain level of data accuracy and data 

quality is required to use these analytical tools, MDOT’s commitment to use standardized 

roadway and crash data found in the Model Inventory of Roadway Elements (MIRE) and Model 

Minimum Uniform Crash Criteria data standards help maintain the required data quality levels. 

MDOT is starting to develop and plans to implement a work-order-based maintenance 

management system. While it will take several years for full implementation, eventually this 

system will allow MDOT to capture and maintain data about roadway safety features not 

previously available. The Department will identify a steward for this system and anticipates 

significantly increased data quality for safety programs with its implementation. 

MDOT is in a strong position to use IT to support and improve all segments of its business

operations, especially in the area of safety. A partnership and communication exists between 

the IT office and other business areas (including safety), and their formalized data governance 

structure supports data business planning. Within their current structure MDOT is working to 

provide hardware and software that meet the agency’s business needs. When developed, their 

data business plan will continue to improve communication and collaboration between the 

safety business areas and IT offices to ensure the design of system applications that meets the 

needs of multiple users across the organization.

 

1 http://www.webopedia.com/TERM/Joint_Application_Development.html
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MDOT’s data governance practices continue to improve management of data throughout the 

department by using data in multiple applications. At MDOT, the implementation of data 

governance has a purpose: to put data in a form that can maximize business intelligence and 

data sharing. In addition to making more data readily accessible by using web- and GIS-based 

applications, the Department has made significant investment in identifying the roles and 

responsibilities necessary to oversee and support their data governance structure. 

Michigan Safety Data Management Benefits 

Many of the benefits Michigan has received from data management efforts have resulted from 

statewide adoption of a common LRS. The Michigan State Police originally developed the data 

management efforts; it has directly led to the integration of crash data and road data all public 

roads, regardless of ownership or jurisdiction. There have been several positive “externalities” 

made possible by the integration, such as the integration of MDOT’s management systems, 

including the Safety Management System.

More recently, Michigan’s Transportation Asset Management Council has assessed federal aid 

road conditions using software used by public road agencies, based on the statewide linear 

referencing system. This activity has leveraged the development of software, “RoadSoft,” a GIS 

based roadway management system, including road crashes and safety analysis. While 

“Roadsoft” predates the MIRE, many of the elements are in Roadsoft because they are usefully 

in everyday management of assets. 
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APPLICABILITY TO OTHER STATES

Other states may learn from the MDOT experience in data governance to develop and 

implement similar data governance practices for their safety programs. This comprehensive 

effort includes the participation of people, business processes, and information technology 

tools. Establishing roles and responsibilities for data governance help to embed these practices 

into the culture and day-to-day business operations, which supports the overall Safety Program 

at an enterprise level. Information technology is an important component to support data 

governance initiatives. Whenever possible, it is particularly important to use tools associated 

with GIS and a common LRS for integration of data. The GIS/LRS component not only 

facilitates data integration but it also provides a means to improve data quality through analysis 

using data visual platforms such as mapping. 

Data governance is most successful when business offices and IT offices work as partners to 

ensure that (1) business offices define their IT related needs, and (2) the IT offices procure the 

appropriate hardware and software to meet the agency’s business needs. MDOT has 

successfully utilized the IT services provided by Michigan’s Department of Technology, 

Management and Budget to support the needs of the Safety Program. 

Some examples of the practical benefits realized by MDOT using data governance to strengthen 

data management practices (especially those needed for safety data systems) include the 

following:

• The “collect once, (store once), use many times” policy discourages use of independent 

databases and encourages the use of processes to reduce redundancy in 

collecting and maintaining data. 

• A Data Governance Council is valuable to establish and enforce data governance 

policies at the enterprise level, which results in clear identification of data 

governance policies, procedures, and responsibilities at the agency. 

• The Chief Data Steward role provides perspective for database design and application 

development across an entire enterprise, not just for a specific business area.

• Data stewardship roles throughout the organization help define business rules for 

governing data in each business area, which eliminates confusion over which office is 

primarily responsible for which data system(s). 

Other states can derive similar benefits by implementing the following data governance 

practices:
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• Establish a Data Governance Council via a charter to define the authority of the Board 

to oversee data management practices, policies, and procedures that support the Safety 

Program.

• Determine the roles and responsibilities for data governance. This clarification

eliminates confusion over which offices or business areas are responsible for what 

aspect of the agency’s data governance structure. Roles that should be defined and 

assigned, include the data steward, data custodian, business owner, and data stakeholder

Communities of Interest for the data systems used to support the Safety Program.

• Develop a glossary or dictionary of commonly used business terms to help others 

(including IT staff) understand how commonly used terms (e.g., location data) are 

handled by business units. This lexicon will assist IT staff design database models with 

data dictionary definitions that more closely reflect the common use of data across the 

organization.

• Involve the data stewards in the review of bids and purchases related to IT, software, 

and data management that support the applications managed by those stewards.

• Capture user needs, within the organization, and ensure their understanding across the 

agency. This effort will translate into the implementation of business practices and data 

systems that support user needs, especially needs related to the safety program.

• Update job descriptions and classifications to include the roles of data stewardship and 

relate this concept to employee performance plans or job duties.

• Begin implementing data governance by using information technology and analytical tools 

that are available and easy to understand. It may not be necessary to purchase new 

tools to implement data governance policies, procedures, and standards.

• Highway safety is a great starting point to implement data governance initiatives. There 

is widespread interest in highway safety and therefore, this area offers an ideal

opportunity to reach consensus among groups in respect to the need to improve safety 

and to improve the management of underlying data systems that support the Safety 

Program. 
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RESOURCES

The position of Chief Data Steward at Michigan DOT is one-hundred percent (100%) state 

funded. This helps ensure the position’s duties are within the scope of all program areas and 

not limited to specific activities based on the funding type.
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REFERENCES

The following sources aided in developing this case study.

• Phone interviews and email conversations with: 

− Ron Vibbert, Chief Data Steward, Michigan DOT 

− Dean Kanitz, Safety Data Analysis Engineer, Michigan DOT

− Rob Surber, Office Director of Department of Technology, Management and Budget 

(Enterprise Management Solutions) 

• NCHRP Report 666: Target-Setting Methods and Data Management to Support 

Performance-Based Resource Allocation by Transportation Agencies (Section I: Chapter 4, 

page I-58), http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_666.pdf. 

• Snyder, R. (2013). Data and Information Sharing, Management and Governance Executive 

Directive No. 2013-1, 

Anita Vandervalk, Dena Snyder, Kim Hajek, Talena Adams, and Lisa Smith from Cambridge 

Systematics, Inc. performed this project.

FHWA, Office of Safety 

Stuart Thompson, P.E. 

Federal Highway Administration 

202-366-8090 

Stuart.Thompson@dot.gov

http://safety.fhwa.dot.gov/rsdp/