Data
Business
Plan
Minnesota
Department of
Transportation
Letter from the Business Information
Council Chair
“… cutting across functional area silos and
individual product lines… more effective
frameworks are needed to identify, provide and
sustain those critical data and decision support
systems required for transportation business
decisions.”
– Tim Henkel, October 2007
Data and information are assets that help the Minnesota Department of
Transportation fuel decisions and inform policy, planning, program investment,
design and maintenance operations choices. However, data and information
program investments are made on a project-by-project basis without sufficient
consideration of overall strategic business needs. Fortunately, business
information planning has emerged as a structured process for focusing data
efforts and governing data and information in ways that provide on-going value.
In 2008, Mn/DOT senior management began a business information planning
process to strengthen the alignment between business needs and the many
investments that could be made to sustain, enhance and expand data programs
and information systems. A Business Information Council formed to oversee the
process and development of recommendations contained in the Data Business
Plan for Mn/DOT. This work was additionally identified as a flagship initiative in
the department’s Strategic Plan in 2009.
This Data Business Plan documents the recommendations of the Business
Information Council. It provides background information on data challenges and
issues, recommends a vision and mission for data and identifies principles for
effective data and information management. The plan includes recommendations
and strategies to address high-priority data and information gaps, optimize
Geographic Information Systems and implement data governance.
I would like to thank the many individuals who contributed to the development of
Mn/DOT’s first Data Business Plan. Your leadership will ensure that data and
information are valued and managed assets of the department well into the
future.
The Minnesota Department of Transportation
3
4
Letter from the Business Information Council Chair
Contents
3
Letter from the Business Information Council Chair
7
8
10
Executive Summary
Data Business Plan recommendations
Conclusion
13
13
13
15
16
16
16
Chapter 1: Introduction
Background
Data challenges and opportunities in Mn/DOT
Why develop a business information plan?
Business information planning in Minnesota
Vision
Mission
19
19
19
23
25
26
28
30
32
35
39
Chapter 2: Assessing the current state of data at Mn/DOT
Background
Process
Infrastructure preservation findings and recommendations
The core principles of asset management
Examples of Infrastructure Preservation Data Gap Needs
Traveler safety findings and recommendations
Examples of traveler safety data gaps and needs
Mobility findings and recommendations
Additional Priority and data gaps and needs
Concluding thoughts on data gaps and needs
41
41
42
42
44
44
45
45
47
48
49
51
51
52
52
53
Chapter 3: Data Governance
Background
Data governance framework
Principles
Policies
Standards
Roles
Data governance board
Data Stewardship Steering Committee(s)
Data stewards
Data management coordinator
Processes
Integration with the division directors’ investment management process
Department IT architecture
Business data catalog
Conclusion
55
55
Chapter 4: Geographic Information Systems introduction
Background
The Minnesota Department of Transportation
5
55
57
57
58
60
61
63
63
63
66
67
GIS industry directions and trends
A tool in the toolbox
Identify core geographic information system spatial data needs
Provide strategic direction for GIS to address business needs for
geospatial data
Strengthen GIS business support
Align data governance and GIS
Vision
Goals
Objectives
Strategic planning for GIS
Conclusion
69
Chapter 5: Conclusion
71
71
71
72
Appendix 1: BIC-GIS Members
BIC-GIS Work Team:
GIS Strategic Plan Revision Participants:
Mn/DOT Business Information Council
75
76
78
80
Appendix 2: Summary of Survey Results
Preservation Business Emphasis Area
Mobility Business Emphasis Area
Safety Business Emphasis Area
71
Appendix 3: Mn/DOT Data Management Principles
75
Appendix 4: Metadata Element Standards
65
65
65
66
66
Appendix 5: Data Governance Role Responsibilities
Data Governance Board
Data Stewardship Steering Committee
Data Stewards
Data Management Coordinator
67
Appendix 6: Complete List of Data Management Roles
6
Contents
Executive Summary
In 2008, the Minnesota Department of Transportation (Mn/DOT) initiated a
process to develop a business plan for data. The purpose of the plan was to
strengthen the alignment between data program investments and the business
needs of the department.
The data business planning process provided a framework to respond to growing
transportation data and information gaps and requirements. In addition, it
provided a platform for considering how stronger data management practices
can:

Increase transparency and accountability

Expand the reliability and utility of data to meet business decision making
needs

Create efficiencies in accessing, sharing and using data and information

Standardize processes and systems that reduce redundancy and promote
consistency of data

Optimize new information management and spatial data tools and
methods
Mn/DOT created a Business Information Council to serve as the leadership body
for the development of the Data Business Plan. Council membership included
senior managers and representatives from districts and specialty offices
throughout the department. Cambridge Systematics, Inc. was retained and
provided leadership to business information planning efforts. In 2009, the entire
data business planning effort was identified as a flagship initiative in the
department’s Strategic Plan.
The data business planning process resulted in a new vision and mission for
guiding Mn/DOT data and information programs.
Vision
All Mn/DOT business decisions will are supported by reliable data
Mission
Provide reliable, timely data and information that is easily accessed,
shared for analysis and integrated into Mn/DOT’s decision-making
process
The Minnesota Department of Transportation
7
Data business planning also identified seven key principles for managing all
future Mn/DOT data and information system investments. These seven principles
declare that throughout the department:
1.
2.
3.
4.
5.
6.
7.
8.
Data will be managed as state assets
Data quality will fit its purpose
Data will be accessible and shared as permitted
Data will include standard metadata
Data definitions will be consistently used
Data management is everybody’s responsibility
Data shall not be duplicated
Data Business Planning Tracks
Three separate tracts were implemented to accomplish data business planning
activities.
Data Business Planning Tracks

Assess the current state of data and information and identify priority gaps
and needs for infrastructure preservation, traveler safety and mobility

Strengthen data governance principles and processes

Validate and provide additional strategic direction for optimizing GIS in
department business processes
Personnel from throughout the department were involved in surveys, meetings,
work team and focus groups to discuss opportunities, constraints and challenges
associated with each of the three data business planning tracks. From these
efforts a series of recommendations and suggested strategies were identified to
strengthen data and information programs at Mn/DOT. Recommendations and
strategies were presented to the Business Information Council. Those identified
as priorities for implementation are summarized on the following pages.
Data Business Plan Recommendations
Data Gaps and Needs
1. Develop an asset management framework for Mn/DOT (pg. 24)
8
Executive Summary
2. Improve the accuracy and completeness of statewide roadway inventory
data for safety analysis (pg. 29)
3. Determine the performance metrics, data and information needed to
implement a programmatic multimodal approach for addressing mobility,
travel time reliability and accessibility for passengers and freight travel
(pg. 32)
4. Increase the data and information available on travel behavior and mode
choice (pg. 34)
5. Strengthen the financial data available for making business investment
decisions (pg. 36)
6. Provide more timely and easily accessible information on the status of
transportation projects and planned work activities (pg. 37)
7. Implement “business intelligence” and solutions, as well as tools to
provide a more efficient and cost-effective means for managing, analyzing
and integrating Mn/DOT data (pg. 38)
8. Institutionalize processes and methods for revisiting critical business data
gaps and needs on a continuing basis (pg. 40)
Data Governance
1. Formally adopt the data governance principles identified in the Data
Business Plan and incorporate them into policies, standards and
processes (pg. 43)
2. Revise existing policies (e.g. stewardship, development, data and
security, database recovery, data retention) and develop additional
policies needed to implement data governance at Mn/DOT (pg. 44)
3. Adopt or revise existing standards (e.g. metadata element, naming
conventions, physical data modeling) and develop additional standards
needed to mature data governance at Mn/DOT (pg. 45)
4. Replace the BIC with a seven-member Data Governance Board, which
will include the CIO and Data Management Coordinator (pg. 46)
5. Create the Data Stewardship Steering Committee role as part of the larger
data governance program (pg.47)
6. Formalize the Data Steward role as part of the data governance program
(pg.48)
7. Assign the Data Management Coordinator role within Mn/DOT (pg. 50)
8. Develop a process to integrate and create touch points between data
governance and Division Directors’ investment management (pg. 51)
9. Implement department-wide IT architecture at Mn/DOT (pg. 52)
10. Initiate a project to implement a Business Data Catalog (pg. 53)
The Minnesota Department of Transportation
9
Geographic Information Systems (GIS)
1. Undertake a formal assessment of currently available GIS data and
determine what are essential or core data, and where there are gaps and
needs (pg. 57)
2. Establish an entity to recommend and steer the development and review
of GIS-related projects, initiatives and investments to the Division
Directors’ “snake” process (pg. 59)
3. Create a GIS Business Support Unit consisting of GIS professionals to
assist users with the production of maps and analytical needs beyond
desktop business support tools (pg. 60)
4. Identify and implement effective methods for periodically convening
spatial data stewards and users to get input on opportunities and
imperfect processes and share information on innovations and data
concerns (pg. 61)
5. Develop processes to manage GIS technology improvements and GIS
data investments, integrity and data accuracy decisions to ensure they
are balanced against the business needs for which they are intended (pg.
63)
6. Implement geospatial data governance formats and protocols and
geospatial technology that allow for sharing of geospatial data with
partners and stakeholders to achieve necessary accessibility and ensure
data quality, consistency and integrity (pg. 64)
7. Update the GIS Strategic Plan approximately every five years, or as the
technology evolves to require an update — furthermore, a GIS Work Plan
should be created every biennium to specifically direct tactical
deployment and budget investments in deploying a department-wide GIS
(pg. 66)
Conclusion
Mn/DOT’s Data Business Plan represents the department’s first attempt to look at
strategic data and GIS needs. Plan recommendations and strategies provide a
solid starting point for enhancing safety data, incorporating asset management
approaches, addressing mobility data needs and optimizing Geographic
Information Systems. Plan recommendations also provide a comprehensive data
governance framework for clarifying roles and responsibilities, setting data
standards and policies, and managing data in ways that reduce redundancies
and promote efficiencies. In addition, the plan recommends the establishment of
a new permanent Data Governance Board to lead the implementation of
recommendations and provide oversight for future data business planning efforts.
10
Executive Summary
Implementing the recommendations in the Data Business Plan will require
continued work and resources over the next two years and cultural changes in
how data and information assets are managed in the department. Over time,
these recommendations will lead to a future where data and information are
managed as true department assets. Organizational structures and processes
will be in place to eliminate unnecessary data and direct investments to data
programs that best support overall multimodal policy, planning, program and
investment decisions.
The Minnesota Department of Transportation
11
12
Executive Summary
Chapter 1: Introduction
Background
Transportation departments throughout the country rely on strong data and
information programs to support decision making. Major investments have been
made in bridge and pavement data management systems to support
transportation planning and infrastructure investment analysis. Support systems
rich with data also have evolved to help with core project development, financial
management, construction and maintenance operations business processes.
The reliance on data and information-based decision making is increasing as
transportation departments strive to be more transparent and accountable.
Performance measurement, streamlining, cost estimating, asset management,
multimodal planning and new mobility, accessibility, sustainability and livability
initiatives are driving expanded needs for timely, accessible and reliable data and
information.
Along with expanding data and information requirements comes the growing
need for stronger data governance, better analytical tools and more accessible
and integrated information systems. Evolving information technology applications
are coming online that can facilitate more informed trade-off analyses and permit
more comprehensive scoping of the anticipated benefits, costs and impacts of
decisions on transportation systems, neighborhoods and the environment.
While transportation data needs are growing, increased funding for data and
information programs is challenging. The Data Business Plan is being developed
to provide a framework to better leverage the utility of existing data and
information and optimize new investments to best meet the department’s
strategic objectives and business needs.
Data challenges and opportunities at Mn/DOT
Effective processes are in place at Mn/DOT for guiding information technology
investments. Yet, overall strategic direction for department data and information
collection and management has been limited. This has resulted in a situation
where:
1. Many data systems are independent and lack interoperability
2. Data program investments are often made at the functional vs.
organizational level so that overall agency needs are not always
optimized
3. Not all data are easily accessible, so it is hard for users to find what they
need
4. Many data sets have limited analysis, query and predictive capabilities
The Minnesota Department of Transportation
13
5. Not all data have geographical coordinates, making it difficult to do spatial
data analysis
6. Core data (e.g. financial, traffic, crashes, roadway characteristics) reside
on older legacy systems that will require substantial reinvestments to fully
meet current and future business needs
7. There are redundancies in data collection and data management system
efforts
8. Major data initiatives have been started, but not fully completed
There are new emerging needs for data to support multimodal planning,
performance management and new livability and sustainability initiatives
In addition, there is a lack of governance in place for effective data management.
A data governance framework can clarify and institutionalize data owner and
stewardship roles and responsibilities, reduce redundancies and improve data
reliability. Instituting data principles, standards and processes as part of a data
governance framework can additionally improve data consistency, utility and
interoperability to meet broader business needs.
In recognition of these issues, Mn/DOT management began describing a different
future for how data and information could be managed within the department.
They described a future scenario where:
1. Data and information are managed as department assets with value tied
to use
2. Frameworks are in place for understanding what data make a substantive
difference in policy, planning, program and project decisions – and which
do not
3. There is consensus on the level of data integrity required – driven by
business needs
4. There are better tools for converting personal knowledge into institutional
knowledge
5. Data sharing extends value, reduces redundancies and promotes
efficiencies
6. Electronic access to shareable data promotes broader use and more
effective decision making
7. Department-wide solutions facilitate data sharing
8. Data governance principles, processes and standards increase the value
of data for all users
9. Business information planning was chosen as the method for moving the
department forward in achieving this future scenario
14
Chapter 1: Introduction
Why develop a business information plan?
Data business plans are becoming important structural elements of transportation
organizations. They can help organizations manage data assets by providing
qualitative processes for assessing the value of data to the organization. Plans
also can provide programmatic approaches for focusing data efforts, eliminating
unnecessary data efforts and reducing redundancies. In addition, they can
provide a structure for governing and managing data and information that provide
on-going value.
Several state transportation agencies have or are in the process of developing
data and information business plans:
1. Florida identified information, resources and technology needs for
meeting new intermodal system requirements.
2. Kansas has data business plans that bring business area and information
technology specialists together to address agency data needs.
3. Virginia completed a data business plan for its systems operations in the
operations planning division.
4. Alaska is continuing work on a data business plan to address data
program and system integration needs.
5. Michigan began a data business planning effort to identify and reach
consensus on key principles for managing data in the organization to
address needs and promote system efficiencies.
6. Washington created a data council that brings together business and
information technology staff to discuss information needs, issues and
strategies.
These states are leading a growing national recognition that data business
planning can provide solutions in an environment where competition for scarce
resources put even greater pressures on transportation data programs.
“As transportation choices become more complex, the challenge to supply
useful, timely and understandable data and analyses to inform
transportation choices becomes even greater. At the same time, budget
pressures can make it difficult to sustain essential data programs.”
– Deb Miller, Secretary of the Kansas DOT, TRB Circular 121,
August 2007.
The Minnesota Department of Transportation
15
Business Information Planning in Minnesota
In February 2008, Mn/DOT division directors approved a proposal to launch a
business data and information planning effort to:

Develop a high-level vision and mission for managing data and
information

Identify and prioritize data and information gaps and needs

Strengthen data governance principles and frameworks to more
Effectively manage information

Validate Mn/DOT’s strategic plan for GIS

Prepare a business information plan with recommended strategies and
actions to achieve the department’s data and information vision and
mission
The data and information business planning effort became a leadership flagship
initiative in Mn/DOT’s Strategic Plan of 2009.
The department created a Business Information Council to provide direction to
business data and information planning efforts. The council included
representatives from all major functional areas of the department, including
district offices (Appendix 1 includes a full listing of members).
The Director of the Modal Planning and Program Management Division chaired
the Business Information Council. The Office of Transportation Data and Analysis
and the Office of Information and Technology Services collaborated on project
management and a business consultant, Cambridge Systematics, Inc., provided
leadership and technical assistance to the project.
Vision
All Mn/DOT business decisions will are supported by reliable data
Mission
Provide reliable, timely data and information that is easily accessed,
shared for analysis and integrated into Mn/DOT’s decision-making
process
16
Chapter 1: Introduction
Following the development of a vision and mission, the Business Information
Council identified the following three tracks for guiding Mn/DOT’s first business
information planning effort:
1. Assess the current state of data – identify data and information that are
important to achieving Mn/DOT business-emphasis-area outcomes for
infrastructure preservation, traveler safety and mobility; determine where
there are priority gaps and needs; recommend factors for determining
future data and information investments
2. Strengthen data governance – begin developing principles, policies,
standards, strategies and methods for clarifying data governance roles
and processes
3. Validate strategic objectives and plans for GIS – validate the
department’s current GIS strategic plan, identify key trends and
opportunity areas and develop a tactical work plan that outlines priorities
and next steps for optimizing the value of spatial data tools and
technologies in business processes
The remainder of the plan outlines the processes, findings, results and
conclusions of the work accomplished in each of these track areas. It also
highlights recommended priorities and next steps for strengthening Mn/DOT data
and information programs consistent with approved department data
management principles and data governance framework.
The Minnesota Department of Transportation
17
18
Chapter 1: Introduction
Chapter 2: Assessing the current
state of data at Mn/DOT
Background
Assessing the current state of data at Mn/DOT and identifying priority data and
information gaps and needs were primary objectives of the overall data business
planning effort. This chapter of the Data Business Plan outlines:

The process that was followed to understand what data are important to
achieving desired performance outcomes

How well data are meeting current and near-future business needs

Where the department can be doing more

Where the department can be doing less and how data collection and
information management can be more efficient and less redundant
Process
The framework illustrated in Figure 2-1 became the foundation for aligning
department missions, strategic directions and statewide transportation plan
policies with the assessment of data at Mn/DOT. The following three key
business emphasis areas and their associated performance objectives/outcomes
were chosen for the initial assessment of data gaps and needs at Mn/DOT:
Infrastructure preservation – ensure the integrity of the transportation
systems serving people and freight
Traveler safety – reduce the number of fatalities and serious injuries for
all travel modes
Mobility – provide mobility, address congestion and provide for the
changing transportation needs of people and freight in greater Minnesota
and metropolitan areas
In assessing data gaps and needs, consideration was given to all of the data and
information required to plan, produce, operate/maintain and support the
performance objectives and outcomes for each of these emphasis areas.
Chapter 2: Assessing the current state of data at Mn/DOT
19
The process for assessing the current state of traveler safety, infrastructure
preservation and mobility data and information at Mn/DOT was made up of four
key steps:
Step 1 – Survey data users
In July 2009, a survey was conducted to assess the current state of data at
Mn/DOT. It was based on a survey completed at the Virginia Department of
Transportation, but customized for use at Mn/DOT. The survey was sent to all
Mn/DOT managers and supervisors who were encouraged to complete, delegate
or forward the survey as appropriate.
The survey sought to: determine which data programs are essential, helpful or
not needed for business decisions; identify which data programs are not meeting
the needs of the users; and assess the characteristics of the data programs to
determine why they may not be meeting needs.
Modeled after the Virginia DOT’s data survey, Mn/DOT identified 35 data
categories to be assessed that supported the business emphasis areas of
preservation, mobility or safety. In order to facilitate the completion of the survey,
the categories were organized into the following six groups:
1. Road-related data – construction plans, crashes, pavement conditions,
roadway centerline mileage and characteristics, roadway intersections,
roadway maintenance and traffic
2. Road-related asset infrastructure data – bridges, railroad grade
crossings, other road infrastructure, signals and lights, signs and transit
facilities
3. Road-related asset operations data – bridge operation, other road
infrastructure operation, signals and lighting operation, signs operation
and transit operation
4. Non-road asset infrastructure data – aeronautics infrastructure,
facilities infrastructure, fleet condition, hydraulics infrastructure and rail
infrastructure
5. Non-road asset operations data – aeronautics operation, facilities
operation, fleet operation, hydraulics operation and rail operation
6. Support data – demographic, economic, environmental, financial, human
resources, planned work, surveying/mapping and weather
A total of 264 survey responses were received from personnel throughout the
department. Survey results provided good clues about where the department
could be doing more to strengthen data and information programs to support
traveler safety, infrastructure preservation and mobility objectives and outcomes.
Step 2 – Conduct focus groups
Following the survey, individual traveler safety, preservation and mobility focus
groups were created to discuss survey findings and results.
20
The Minnesota Department of Transportation
Figure 2.1: Data Business Plan framework for accessing the current state of data at
Mn/DOT
Chapter 2: Assessing the current state of data at Mn/DOT
21
Each focus group consisted of Mn/DOT professionals involved in achieving
performance objectives and outcomes for each of the three emphasis areas.
Each group met up to three times with a varying number of participants. The
intent of the focus groups was to:
1. Discuss and expand on survey results
2. Identify any additional or future data needs
3. Clarify areas of concern related to any planning, production, maintenance
and operations, and support data required to achieve emphasis-area
work activities
4. Agree on prioritized areas of concern and needs
5. Identify how data gaps and needs tie back to performance measures of
mobility, preservation and safety
6. Recommend areas of improvement, solutions and priorities
Based on survey results and personal knowledge of data gaps and needs, each
of the focus groups identified several high-priority opportunity areas and solutions
for improving department data and information programs to better achieve
department objectives and performance outcomes for safety, preservation and
mobility.
Step 3 – Scope opportunities for improvement
In this step, data owners, Data Stewards and Information Technology staff met to
discuss the high-priority opportunity areas recommended for improvement by the
focus groups. Based on their understanding of data and information systems,
they scoped the potential people, process and technology implications of
possible solutions. From there they recommended practical and sustainable
strategies and actions for addressing priority data and information gaps and
needs consistent with the data management principles and data governance
framework (outlined in Chapter 3 of this plan).
Step 4 – Determine priorities for calendar year 2011,
2012
In this last step of the process, factors were identified for determining priorities
among all of the strategies and actions recommended for improving the data and
information available to support traveler safety, infrastructure preservation and
mobility.
The Business Information Council applied a peer comparison process, facilitated
by Decision Lens, and recommended a list of data and information improvements
for calendar years 2011 and 2012 to be included in the Data Business Plan.
The following summarizes process results for each of the business emphasis
areas of traveler safety, infrastructure preservation and mobility and outlines
22
The Minnesota Department of Transportation
those recommendations and strategies that were identified as high priorities for
the first data business planning effort.
Infrastructure preservation findings and
recommendations
Infrastructure preservation refers to all the activities the department engages in to
preserve the functionality of the transportation system. The key performance
objective and outcome for infrastructure preservation is to ensure the integrity of
the transportation system that serves people and freight.
Results of the survey on data gaps and needs suggest the top 10 types of data
deemed most essential in achieving infrastructure preservation work objectives
include:

hydraulic infrastructure data

construction plans

traffic data

roadway centerline data

financial data

bridge infrastructure data

data on planned work activities

human resources data

pavement condition data

surveying and mapping data
On the positive side, more than 70 percent of respondents indicated that
pavement data are fully meeting their needs. Sixty percent of respondents
indicated that bridge infrastructure data fully meet their needs.
Of the data identified as most essential, the completeness of hydraulic
infrastructure and utility data were seen as the most significant issues to fully
meeting infrastructure preservation user needs. The completeness of data on
signs and rail infrastructure were also cited as not fully meeting user needs.
Focus group participants reviewed survey results and discussed opportunities for
improvement. In the assessment of data gaps and needs, the focus group limited
discussion to the preservation of infrastructure located within state trunk highway
system right of way. In the long term, a broader assessment will be required to
address infrastructure preservation needs for all transportation modes as well as
Mn/DOT’s physical assets located off the right of way (e.g. truck stations, radio
towers).
Focus group participants identified three priority areas for developing
recommendations and strategies. These priority areas were forwarded on
business data owners and stewards for further scoping. Resulting
Chapter 2: Assessing the current state of data at Mn/DOT
23
recommendations and strategies were then ranked by the Business Information
Council using a peer review process to determine the highest priorities for further
work in calendar years 2011 and 2012.
The development of a department-wide framework for asset management was
identified as the highest priority. The following summarizes a recommendation for
asset management and suggested strategies for accomplishing the
recommendations:
Recommendation 1: Develop an asset management framework for
Mn/DOT
Suggested strategies:
A. Develop an agency-wide multimodal framework consistent with FHWA
and AASHTO best practices to promote asset management best practices
in capital investment, maintenance, and system design — establish longterm asset management objectives and develop strategies for meeting
these objectives — define department organizational roles and
responsibilities for coordination and oversight of implementation
B. Evaluate asset management efforts currently underway (e.g. signs,
pavement markings) to determine resource needs for completing work
activities
C. Determine which assets are high-priority candidates for being part of a
department asset management system and what attributes should be
collected for included assets; this includes those for which data are now
required by federal and state requirements
D. For transportation assets that are not currently inventoried or tracked,
develop a methodology to assess the benefit and return on investment for
establishing inventories to track age, condition and other attributes
E. Review technology options and identify a solution that can effectively
meet asset inventory data and information needs and maintenance work
management objectives
F. Identify GPS field data collection standards and GIS data formatting
standards to ensure that asset information is collected at the desired
accuracy and consistency so that it is shareable within the department
and with Mn/DOT partners and stakeholders
24
The Minnesota Department of Transportation
The core principles of asset management

Policy-driven — Resource allocation decisions are based on a welldefined set of policy goals and objectives.

Performance-based — Policy objectives are translated into system
performance measures that are used for both day-to-day and strategic
management.

Analysis of options and tradeoffs — Decisions on how to allocate
funds within and across different types of investments (e.g. preventive
maintenance versus rehabilitation, pavements versus bridges) are
based on an analysis of how different allocations will impact
achievement of relevant policy objectives.

Decisions based on quality information — The merits of different
options with respect to an agency’s policy goals are evaluated using
credible and current data.

Monitoring provides clear accountability and feedback —
Performance results are monitored and reported for both impacts and
effectiveness.
Adapted from NCHRP Report 551, Performance Measures and Targets for Transportation
Asset Management, Vol. I, Research Report, 2006, p. ii.
Rationale:
Mn/DOT has implemented asset management approaches for managing data on
pavements, bridges, signs, hydraulic structures, lane markings and other
department assets. However, no uniform framework has been developed to
identify where it makes the most sense to expand asset management data
collection efforts.
In addition, data on some assets, such as right-of-way limits, are only available in
archaic paper formats that are not as useful as they could be in an era of
electronic information sharing. Other existing data on assets are being stored in
silo systems that do have good integration and/or interaction with each other.
Also, limited standards for data collection and formatting means that data are not
always collected and managed in ways that are sustainable over the long term or
designed to meet multiple business needs across the organization. As data on
infrastructure assets become more prevalent, the department should consider
which information system technology options can best manage overall asset data
and information to comply with data governance principles and provide easy
access, effective analysis, data sharing and interoperability between different
asset management inventories.
Chapter 2: Assessing the current state of data at Mn/DOT
25
Examples of Infrastructure Preservation Data Gaps and
Needs
→ Complete the statewide inventory of hydraulic
infrastructure features and enhance management of
hydraulic infrastructure data
The inventory and inspection of centerline culverts has been identified as a highpriority project for the last several years. Funding to assist districts in completing
the inventory and inspection work was provided by Chapter 152 funds. The
majority of the culvert inventory work has been completed. Continued funding
may be necessary to: complete the centerline culvert inventory, perform routine
inspections in order to keep data up-to-date and inventory and inspect other
hydraulic assets in order to maintain the system and meet permit requirements.
At the same time, the hydraulic infrastructure database currently being used to
store and provide access to these data would benefit from some short-term minor
repairs to improve functionality.
Immediate short-term needs could be followed by a more major effort in the next
2-3 years to incorporate more life-cycle analysis and planning in order to help
project managers determine the most cost efficient ways to maintain data on
hydraulic infrastructure components. In addition, some districts would like to have
functionality to track additional information for hydraulic assets included in the
existing hydraulic infrastructure database, as well as additional assets such as
edge drains. There also is a need for some districts to be able to develop
additional functionality to more easily add and use storm drain information.
The need for more accurate and comprehensive hydraulics data is being driven,
in part, by external requirements. Regulations put forth by the Environmental
Protection Agency and the Minnesota Pollution Control Agency will oblige
Mn/DOT to conduct regular inspections of storm water retention ponds and other
hydraulic infrastructure. Some suggested strategies and actions for
accomplishing this include:
26

Continuing to encourage district completion of the inventory of centerline
culverts

Identifying a funding source for the inventory work when current funds
(Chapter 152) are no longer available

Implementing a few minor repairs to the database to make it easier to use

Bringing together stakeholders to analyze data gaps and identify what
could be done over the long term to increase the functionality of the
database and make the data more useful for life-cycle planning, drainage
analyses and system analysis — enhancements may include adding
functionality to keep track of repairs and condition inspections and/or
expanding optional asset inventories for storm sewers and edge drains
The Minnesota Department of Transportation
→ Collect and manage location data on Mn/DOT-owned
underground utilities
Within Mn/DOT right of way there are miles of underground cable, pipe and wire
utilities. Knowing where these utilities are is important for project planning,
design, construction and maintenance. In the summer of 2008, the department
had eight fiber cables cut, resulting in costly repairs.
Additionally, the department has obligations under Gopher State One Call to
provide reliable information on the location of underground utilities prior to any
digging in the area.
The Department of Public Safety’s Office of Pipeline Safety oversees the Gopher
State One Call system. They are now requesting that Mn/DOT change its system
of receiving locate notifications so the department will be required to look at all
tickets, even if they are indicated as not being in the right of way. These new
requirements will nearly double the number of tickets to manually review.
An information technology project is underway to replace existing Gopher State
One Call software. The new software will provide enhanced ticket management
and a map viewer of ticket locations. It will begin preparing a database that can
be setup in the department’s transactional spatial data environment. Future
phases of the project are being planned to provide a mobile application for
collecting data on underground utilities and providing tools for field locating utility
inventory data.
→ Collect and manage railroad grade crossing data
There is a need to expand and update railroad grade crossings data collection
and management. The Office of Freight and Commercial Vehicle Operations has
developed a database on highway-railroad grade crossings within the state.
There are approximately 6,500 crossings, of which approximately 4,300 are
public crossings. The information in the database is used to assist in determining
if a crossing should be updated from passive to active (flashing lights and/or
gates). In addition, information on railroad grade crossing locations,
characteristics and elevation is critical in the design of state and local highway
projects. Information also is critical in evaluating whether there are sufficient
stacking distances for traffic in advance of railroad grade crossings.
OFCVO has determined it would be reasonable to update the data on a threeyear cycle or approximately 1,500 crossings per year, although current staffing
limitations prohibit reaching that goal. OFCVO is currently inspecting an average
of 400 crossings per year.
The need to expand and update is driven partly by external requirements. The
Rail Safety Improvement Act of 2008 (RSIA 208), Public Law 110-432, requires
both states and operating railroads to submit data on every public and private
Chapter 2: Assessing the current state of data at Mn/DOT
27
grade crossing annually. Many, but
not all of the data elements, are
similar to those currently collected.
Although it is not practical to collect
data at each of the 4,500 crossings
on an annual basis, modifying the
database to include federally
required data elements and
expanding the data collection effort
would help in meeting this
requirement.
→ Address other Overhead and Underground Utility Data
Needs
A long-term, but increasingly important, need is data on other privately or locally
owned utilities that lie under, over or near state highway rights of way. These data
are critical for road construction and maintenance operations activities. Knowing
the locations and height of overhead utilities also are important for routing over
size and over dimension vehicles. Strategies and actions to meet these needs
will be addressed in future data business plans.
Traveler safety findings and recommendations
Traveler safety refers to all Mn/DOT activities that have an impact on reducing
the number of fatalities and serious injuries for all travel modes. From the survey,
10 types of data were identified as being essential in conducting traveler safety
work activities. These included:
28

data on planned work activities

construction plans

traffic data

crash data

financial data

roadway centerline data

roadway intersection data

pavement condition data

hydraulic infrastructure

surveying and mapping data
The Minnesota Department of Transportation
Of these 10 types of data, those most meeting user needs were bridge
infrastructure data and pavement condition data. Among those least meeting user
needs were crash data and roadway centerline data. The reasons most often
cited for not fully meeting needs were the accuracy in the location of crashes and
the completeness of roadway inventory data for all public roads, particularly
those off the state trunk highway system.
Focus group participants reviewed and discussed survey results. They identified
several recommendations for enhancing the data available for meeting traveler
safety business outcomes. These were forwarded to business data owners and
stewards for further scoping. Resulting recommendations and strategies were
then ranked by the Business Information Council using a peer review process to
determine the highest priorities for further work in calendar years 2011 and 2012.
The highest priority for enhancing data for traveler safety was enhancing the
completeness and accuracy of roadway centerline data. Recommended
strategies to accomplish this include:
Recommendation 2: Improve the accuracy and completeness of
statewide roadway inventory data for safety analysis
Suggested strategies:
A. Identify and prioritize roadway inventory data attributes most important to
traveler safety for vehicles, bikes and pedestrians on state and local
systems — for example, important attributes for safety might include: data
on curves, striped shoulder widths, sharp or flat slopes, interchanges and
intersections, particularly those with high traffic volumes. In thinking about
data needs, it will be important to consider all factors that contribute to
highway safety, including those beyond the edge line.
B. Work with stakeholders and partners to develop methods for collecting
and managing data on new roadway features that are not presently
available — work with Mn/DOT district and local partners to identify
strategies and mechanisms for increasing the accuracy and
completeness of existing data on roadway inventory attributes.
C. Improve the analytical tools available for system-wide analysis to identify
opportunities for preventing fatalities and serious injury crashes
D. Continue to support the Transportation Information System mainframe
replacement project so it can be a reliable and effective source of
roadway inventory data
E. Continue work on the statewide ADA inventory of roadway characteristics
to determine where there are priorities for accessibility improvements
F. Research opportunities for utilizing innovative technologies for collecting
roadway inventory data such as mobile laser scanning and/or remote
sensing
Chapter 2: Assessing the current state of data at Mn/DOT
29
Rationale:
More than 50 percent of fatalities in Minnesota occur on rural two-lane local
roadways. Minnesota’s Toward Zero Deaths Program is committed to addressing
this situation and funding is being made available to address local safety issues.
However, preemptively reducing fatalities and serious injuries on rural local
roadways will require additional information and analysis of contributing factors,
including more complete and accurate information on local roadway
characteristics and conditions.
Mn/DOT’s TIS and the State Aid
Division’s “needs” database are the
current sources of data on local
roadway characteristics. TIS is
scheduled for replacement and
discussions regarding future State
Aid Division information
management needs are underway.
Plans for future system design must
identify opportunities to work
cooperatively with locals to improve
the accuracy and completeness of
local roadway inventory data. In
addition, research on new innovative
technologies for roadway inventory data collection, management and reporting,
such as laser scanning, should continue to be pursued.
Examples of Traveler Safety Data Gaps and Needs
→ Strengthen traveler safety analytical tools and data
research capabilities
No department-wide safety management system presently exists to provide
standard analytical tools to search, query, analyze and report on crash data. A
new “Safety Data Analyst” AASHTOWARE product is coming online soon.
However, it is not expected to meet overall crash and safety analysis needs.
The current source of crash data is TIS. “Synthesized” crash reports from the
Department of Public Safety electronically update TIS on a regular basis. While
TIS does provide crash data for all public roads in Minnesota, there are a number
of limitations associated with this old legacy mainframe system. It is difficult to
download information and almost impossible to enhance. Local governments do
not have direct access to TIS data and there are no feedback loops in place for
notifying DPS or locals when corrections are made to the data. In addition, TIS
and the department’s GIS BaseMap are not integrated to provide long-term
stable mapping capabilities.
30
The Minnesota Department of Transportation
TIS is scheduled to be replaced over the next 2-3 years and integrated with a
new Linear Referencing System. The conceptual future plan for a new TIS/LRS
has crash data flowing from DPS to a new safety management system that has
expanded analysis and reporting capabilities. Priority needs to be given to timely
replacement of the TIS mainframe and development of a new LRS and related
safety data projects.
Possible strategies to improve the analytical tools available for safety analysis
include:

Developing a new safety information management system for storing and
managing crash data records from DPS that provides flexibility to permit
all users to correct data and be notified when revisions are made

Exploring how new “business intelligence” tools can assist in providing
better analytical tools to conduct more robust strategic safety analysis

Continuing to support development of a new LRS and TIS mainframe
replacement project that can be linked to the new safety management
system to provide users with enhanced mapping capabilities and access
to traffic and roadway characteristics
→ Improve the accuracy of data on crash locations and the
timeliness of making data available
Timely and accurate crash data, particularly the location of crashes, are critical
because they help determine what remedial actions might be taken to eliminate
hazards and improve safety. Unfortunately, the accuracy and completeness of
crash records continues to be an issue. Local agency results often vary
significantly from data reported by the state due to differences in what data are
reported and because of better local knowledge on where crashes occurred.
Data on crashes that involve pedestrians and bicyclists also are not always
complete. In addition to accuracy issues, it is taking up to six months or longer for
crash data to be updated and made available for project managers and other
data users. More coordination between Mn/DOT and state and local law
enforcement agencies are needed to revisit crash coding practices and
reemphasize the priority and importance of accurate and timely crash reporting.
Possible strategies for enhancing crash data accuracy and timeliness include:

Revisiting state-level ownership and stewardship roles and
responsibilities for coding and processing crash data

Identifying opportunities to improve reporting of bicycle and pedestrian
accidents

Developing a communication strategy and training process to expand
awareness among law enforcement officers and the public on the
importance of accuracy in crash locations

Identifying specific actions that can be taken to improve the timeliness of
coding, processing and reporting crash data, including taking advantage
of GPS to improve the accuracy of coding crash locations
Chapter 2: Assessing the current state of data at Mn/DOT
31
Mobility findings and recommendations
Mn/DOT mobility objectives and performance outcomes emphasize the need to
provide mobility, address congestion and provide for the changing transportation
needs of people and freight. They focus on improving travel time reliability,
throughput and the accessibility of modal options to meet transportation needs in
Greater Minnesota regions and metropolitan areas.
Survey results indicated that essential data for addressing mobility outcomes
include: traffic data, travel time data, data on planned work activities and financial
data. Survey results were discussed by focus group participants and
subsequently by data business stewards and information technology personnel.
The groups clarified data and information needs and recommended continuing
work on a few key data initiatives, as well as the development of new data and
information strategies to address performance areas related to mobility, travel
time reliability, traveler behavior and accessibility. Recommendations were
forwarded on to business data owners and stewards for further scoping. These
were then ranked by the BIC using a peer review process to determine the
highest priorities for further work in calendar years 2011 and 2012. The mobility
recommendations identified by the BIC as priorities include:
Recommendation 3: Determine the performance metrics, data and
information needed to implement a programmatic multimodal approach
for addressing mobility, travel time reliability and accessibility for all
users of the system
Suggested strategies:
A. Define what performance metrics, data and information are needed to
design, maintain, operate and improve mobility, throughput, travel time
reliability and accessibility for all users and across all modes and regions
of the state
1. Clarify department needs for travel time data, including those
involved in operations and systems management activities
2. Continue to work with the Texas Transportation Institute to refine
travel time index calculations and obtain data on arterial travel
times in the Minneapolis-St. Paul metropolitan area and on key
interregional corridors in Greater Minnesota
3. Review and identify opportunities to use and apply national and
state research on travel time reliability
4. Work with the University of Minnesota, the Metropolitan Council
and other stakeholders to develop operational measures and
identify data needs for understanding how the system is
performing in respect to accessibility
32
The Minnesota Department of Transportation
5. Continue work on the statewide ADA inventory of roadway
characteristics to determine where there are opportunities and
priorities for accessibility improvements
6. Identify options and resource requirements for collecting better
data and information on the “person throughput” of key corridors,
including occupancy counts for automobiles and transit, as well as
volume and tonnage for freight
7. Identify other public and private alternatives for collecting travel
time information
B. Reassess and clarify what data and information are most useful in
determining the best ways to optimize, maintain and operate the existing
transportation system for all modes
1. Reassess the measures and data used to measure nonreoccurring congestion
2. Define what data and information would be useful in helping the
department manage, utilize and optimize the system, including
those local arterials that carry significant traffic, such as Snelling
Avenue and TH 280 in St. Paul, Minnesota
3. Support work at home, mode choice options, the expansion of
park and ride facilities, and other travel demand strategies to
reduce single-vehicle occupancy use
4. Expand the availability of real-time traffic mode choice information
using new social media communication strategies
5. Continue regional freight planning studies and work activities to
understand how the department can better meet freight needs
6. Continue to expand the data available on truck traffic counts and
truck weights to assist in understanding freight travel trends and
needs
7. Develop a programmatic proposal to collect the data and develop
tools to assist the department in making wise planning,
investment, operations and maintenance decisions to address
mobility, travel time reliability and accessibility
8. Identify data standards and build a database for storing travel time
data that can be accessed and edited by Mn/DOT users
throughout the state
Rationale:
Surveys of transportation users indicate that mobility, travel time reliability and
accessibility are becoming prominent indicators of system performance.
Travelers and shippers want to predictably know how long it will take them to
reach their destinations and they increasingly want travel time information and
accessible choices for making their trips.
Chapter 2: Assessing the current state of data at Mn/DOT
33
Making wise decisions about how to best plan, invest, manage and operate the
state’s multimodal transportation system to enhance mobility, travel time reliability
and accessibility requires additional work to further define appropriate
performance outcomes and metrics.
The work also will determine what
data, information, tools and methods
are useful in addressing issues and
opportunities. This includes
identifying ways to best optimize
existing transportation corridors and
services as well as reassessing how
to best measure and respond to
non-reoccurring congestion and
delays.
Research into these areas has been
increasing. For example, the
National Cooperative Highway
Research Program has funded several recent studies on reliability. In addition,
the University of Minnesota has done groundbreaking work on the subject of
accessibility.
New data collection activities are also underway to better understand travel time
reliability. Mn/DOT’s Metro District recently began working with the TTI on a
project designed to capture Global Positioning System speed data and convert it
to travel time data for major arterials in the Minneapolis-St. Paul metropolitan
region and key inter-regional corridors in Greater Minnesota. These data should
help bridge the gap in obtaining travel times on key non-instrumented roadways.
As additional data, information and analysis tools on reliability and accessibility
become available, database development options and data standards would be
helpful to ensure that data collection meets overall user needs.
Recommendation 4: Increase the data and information available on
traveler behavior and mode choice
Suggested strategies:
A. Support completion of the Metropolitan Council Travel Behavior Inventory
to learn more about origins-destinations, trip lengths, purposes and mode
choice.
B. Identify opportunities to update greater Minnesota MPO traveler behavior
and origin-destination data—options might include participating in the next
FHWA National Household Travel Survey or by conducting broader
Mn/DOT travel behavior studies
C. Support national and state research to develop methods for obtaining
data and information to better understand how travelers respond to policy
34
The Minnesota Department of Transportation
changes, such as congestion pricing, transit incentives, increased
telework and the availability of mode choices
Rationale:
Transportation agencies are increasingly being asked about system performance
as it relates to mobility. Answering this question will require richer data and
information on how individual corridors are performing in respect to person
and/or freight throughput.
Managing existing transportation corridors and planning for future needs also
requires data and information on individual travel behaviors and mode choices.
The Metropolitan Council conducts a Travel Behavior Inventory in the
Minneapolis-St. Paul metropolitan region approximately every 10 years to update
key transportation planning information on trips per household, trip purposes and
lengths and travel origins and destinations. The upcoming TBI will also include
on-board transit surveys and information on major trip generators, like the
Minneapolis-St. Paul International Airport.
Up-to-date travel behavior and mode choice data do not currently exist for other
Metropolitan Planning Organizations or regional centers in greater Minnesota.
Mn/DOT support of the Metropolitan Council TBI and further study of options for
meeting greater Minnesota MPO needs for travel behavior data are important for
ensuring that reliable information is available to support transportation planning
for mobility needs.
Additional Priority Data Gaps and Needs
The survey on data gaps and needs provided respondents with an opportunity to
comment on other data and information improvements that could substantially
add value to traveler safety, infrastructure preservation and mobility business
decisions and work activities. Among all of the comments received, there was
consensus for further work in the following six key areas:

Enhance the financial data available to support business decisions

Develop better and easier-to-use data access tools for Mn/DOT
employees inside the firewall and consultants and partners outside the
firewall

Enhance analytical methods and tools for trending data over time and
predicting future conditions

Improve data integration between and among information systems so that
project managers and decisions makers can overlay data elements to get
more of a composite picture of what is happening across multiple
performance, funding and other outcomes

Identify opportunities to more fully utilize and incorporate GIS
technologies in business processes

Improve access to data on planned work activities
Chapter 2: Assessing the current state of data at Mn/DOT
35
Recommendation 5: Strengthen the financial data available for making
business decisions
Suggested strategies:
A. Initiate an agency-wide effort to define business needs for financial data
beyond what is currently being tracked to meet internal financial control
obligations—this includes strengthening the alignment between financial
data and performance metrics
B. Continue to support the implementation of the Statewide Integrated
Financial Tools project and associated new processes for tracking
business financial data to improve transparency, data accuracy and utility
C. Continue efforts to improve project cost-estimating practices and
processes
D. Develop a process for reaching consensus on how the agency
incorporates labor, overhead materials and other costs into the tracking of
activity, product and business process costs
E. Identify more effective ways of communicating how we spend
transportation dollars and what we accomplished through the expenditure
of funds
Rationale:
SWIFT is under way to implement a statewide enterprise resource and
procurement PeopleSoft system that will replace the current Minnesota
Accounting and Procurement System. SWIFT will integrate all of the
administrative functions across Minnesota state agencies, including: contracting,
procurement, accounts payable, accounts receivable, asset management, federal
funds management, project accounting and billing, inventory, payroll and
reporting.
The effort at Mn/DOT will include business process re-engineering to take
advantage of streamlining work and avoiding duplicity in data entry, data creation
and storage. This effort will provide a single source of financial data that will
enable more transparent information about our financial status as well as total
project costs. In the end, the new system will provide a single authoritative
source of financial data for users throughout the department.
While SWIFT will significantly enhance the transparency of financial data for
managing transactional business activities, there are additional needs for
business financial data to assist with:
1. Cost estimating
2. Life-cycle costing
3. Determining return on investment
4. Comparing trade-offs among different program and modal investments
5. Evaluating alternative service delivery options, including out-sourcing
36
The Minnesota Department of Transportation
6. Calculating the impact of investments on strategic objectives and
performance outcomes
A unitized cost system to track and compare costs is difficult to implement
because of the variety of products and services provided by Mn/DOT. However,
how well a project meets program goals is a financial decision, especially during
times of constrained resources. Better financial data and information are needed
to assist the department in making business decisions and communicating the
value of those decisions to constituents.
Recommendation 6: Provide more timely and easily accessible
information on the status of transportation projects and other planned
work activities
Suggested strategies:
A. Continue efforts to provide real-time information on the status of projects
included in the department’s Statewide Transportation Improvement Plan
B. Identify opportunities to make the “major projects” reports more
accessible
C. Assess the feasibility of incorporating and making additional information
within the agency and to the public on the status of local partner
transportation projects
Rationale:
Survey respondents indicated that information on planned work is essential to
meeting performance outcomes for traveler safety, infrastructure preservation
and mobility. The development of an electronic STIP and the work being done to
enhance cost estimating are expected to improve access to up-to-date and more
complete data and information on the status of highway improvements, as well as
their locations, total costs and funding sources.
Recommendation 7: Implement business intelligence and GIS solutions
and tools to provide a more efficient and cost-effective means for
managing, analyzing and integrating data
Suggested strategies:
A. Implement Mn/DOT’s Business Intelligence Strategy by initiating a project
that will lay the groundwork for business intelligence throughout the
department:
1. Establish a Business Intelligence Program
2. Establish a Business Intelligence Steering Committee
Chapter 2: Assessing the current state of data at Mn/DOT
37
3. Establish a scorecard with criteria for determining if business data
is ready for business intelligence
4. Roll out the use of business intelligence in 3-4 business areas that
have varying complexity of data reporting/analysis needs
5. Establish a baseline and repeatable process for implementing
business intelligence in business areas of Mn/DOT
6. Establish Business Intelligence Centers of Excellence to support
ongoing business intelligence growth and maintenance support
7. Establish the technical infrastructure
8. Procure and implement Oracle’s Business Intelligence Suite
Enterprise Edition
9. Establish a data warehouse and a solid strategy for managing it
10. Establish metadata standards
Rationale:
Business intelligence refers to skills, technologies, applications and practices that
allow people at all levels of an organization to access, analyze and share data to
manage the business, improve performance, discover opportunities and operate
efficiently.
Mn/DOT, like many other organizations, faces the challenges of needing to
manage its data in an accurate, timely and integrated manner. Mn/DOT currently
has approximately 248 silo data systems that were built to meet the needs of a
particular business area. While many of these systems may have been
successful in addressing specific needs at the time, the costs associated with
continuing to maintain separate data systems with duplicate data in many cases
is no longer acceptable.
Business intelligence provides the perfect opportunity to transition from a silo
culture to a department culture. The development of a department-wide approach
to business intelligence may offer a solution for integration of critical data to
support business needs.
A department-wide approach to implementing business intelligence will:
1. Provide a centralized and trusted source of Mn/DOT data for analysis,
reporting and performance measurement against the department’s
mission, vision, goals and drive cost efficiencies
2. Present an easy-to-use, accessible site for staff, legislators and
constituents to view Mn/DOT strategies, initiatives, policies and
associated measures
3. Demonstrate transparency and accountability of Mn/DOT objectives and
performance by providing the public information on how key performance
metrics and investment strategies link to the department’s strategic
objectives
38
The Minnesota Department of Transportation
4. Increase the time staff can devote to actual analysis by reducing the daily
time spent on one-off data integration, data quality, data modeling and
report generation exercises
5. Break the cycle of the “IT report factory” where staff contacts IT to
generate reports and analyses by providing a self-service and
personalized environment for the most casual users to the most
sophisticated users’ information
6. Improve the quality, consistency, timeliness and availability of data by
implementing a department-wide data governance strategy and
methodology for access to information
7. Provide staff the ability to easily perform historical, situational and forward
looking analyses— This equates to: “Where have we been?”, “Where are
we now?”, “Where are we going?” and “What If?”
8. Capitalize on existing stakeholder support, staff enthusiasm, and
department momentum identified during the BIC’s Cambridge Systematic
study and Oracle Insight
9. Align with department’s Information Access Technology Strategy to
provide services, web pages, data, maps, reports and documents to
Mn/DOT staff and others
10. Ensure long-term scalability, flexibility and agility to meet the changing
needs of Mn/DOT’s business
Concluding thoughts on data gaps and needs
This first Data Business Plan focused the assessment of data gaps and needs on
three key business emphasis areas of infrastructure preservation, traveler safety
and mobility. It provided a template and process for identifying needs, as well as
strategies and actions to improve data and information available for decision
making.
Across the department, there are other current and emerging data gaps and
needs that go beyond the scope of this plan. Sustained efforts over the longer
term are needed to continually reassess how well data programs are helping
meet overall multimodal business decisions and performance outcomes. In
addition to identifying data gaps and needs, future efforts could be designed to
include a review of key business processes to determine where there are
opportunities to reduce data collection costs and eliminate unnecessary data.
Chapter 2: Assessing the current state of data at Mn/DOT
39
Recommendation 8: Institutionalize processes and methods for
revisiting critical business gaps and needs on a continuing basis
Suggested strategies:
A. Implement a means of periodically assessing critical business data gaps
and needs through a “data congress” or other means of inviting input from
internal functional groups and external partners
B. Establish processes to regularly assess what data are needed, what data
can be eliminated, what data can be provided internally and what data
can be obtained from other public and private sector sources
C. Assign responsibilities for overseeing processes, reviewing gaps and
needs and identifying future priorities to the Data Governance Board
Data management and governance principles and practices can also provide a
framework for addressing department needs for data and information.
The next chapter of this plan outlines a number of recommended strategies and
actions for strengthening the management and governance of data at Mn/DOT.
The data governance recommendations, strategies and actions included in the
next chapter of this plan provide a framework for effectively managing future
investments in data, while enhancing data stewardship and the standards and
processes in place for improving data quality and reliability.
40
The Minnesota Department of Transportation
Chapter 3: Data Governance
Background
Everyone produces, uses or retires data on a regular basis. However, confusion
still exists on how to define “data.” At Mn/DOT, data is a business asset—it is
owned, managed and produced by business functions. The department makes
decisions with data, but also about data. The state of Minnesota uses the
following definition for data:
Data: A representation of facts, concepts or instructions in a formalized manner
suitable for communication, interpretation, or processing by humans or by
automatic means.1
Data is needed to create information, which is used by knowledge workers to do
their jobs. The right knowledge used by the right worker can turn into wisdom.
Without quality data, information and knowledge are suspect and wisdom is
unattainable.
Figure 3.1: Data, information, knowledge, and wisdom hierarchy 2
The benefits of a strong data management program and data governance plan
were identified in the initial meeting of the Business Information Council in 2008:

More transparency and accountability

More efficient ways to locate and take advantage of available data and
information

Better methods to look at and integrate data from multiple sources

Processes and systems that reduce redundancy and promote
consistency in data results

More timely and even real-time data and information
1
Federal Standard 1037C as cited in MN Enterprise Technical Architecture.
2
Based on Bellinger, Gene, Durval Castro, and Anthony Mills. “Data, Information,
Knowledge, and Wisdom.” Systems Thinking, 2004. www.systems-thinking.org/dikw/dikw.htm
Chapter 3: Data Governance
41

More department-wide spatial data tools
A data governance framework helps to strengthen the overall data management
process within an organization by defining the roles and responsibilities for data
stewards, data architects, data coordinators and business owners, along with
other data stakeholders within the context of the existing organizational structure.
These roles and responsibilities must be made easily accessible to staff in the
organization via an established communication method. Many of the same
responsibilities associated with these groups already exist within Mn/DOT, but
may or may not be clearly identified.
The BIC assigned the task of developing an implementation plan for data
governance to the Data Governance Work Team, which is composed of volunteer
members of the BIC. The Data Governance Work Team established, among
other products, a charge, work plan and principles that were all approved by the
BIC. The team identified two tasks that were too big for a volunteer group to
complete—a recommendation for data governance roles and a plan to implement
a data business catalog. To complete the tasks, the team decided to hire an
independent consultant.
The independent consultant began with the best practices outlined in the Data
Management Association’s Data Management Book of Knowledge. DAMA is a
not-for-profit, vendor-independent, global association of technical and business
professionals dedicated to advancing the concepts and practices of information
and data management. DAMA is considered the authoritative source on how to
manage data as an enterprise asset.
The consultant conducted a survey and followed up with focus groups. Based on
this research the consultant provided the recommendations in this chapter
relating to roles and a data business catalog implementation plan.
Data governance framework
According to DAMA, data management is “the development, execution and
supervision of plans, policies, programs and practices that control, protect,
deliver and enhance the value of data and information assets.” 3 Data
governance, the core function of data management, is the “exercise of authority
and control (planning, monitoring, and enforcement) over the management of
data assets.” 4
The Data Governance Work Team developed a framework to aid in the
implementation of data governance at Mn/DOT. The framework begins with the
development of data principles; moves to identifying, revising and creating data
policies; shifts to identifying and creating data standards; then moves to clarifying
the roles relating to data. Finally, the framework looks at the processes that
support data roles, standards and policies.
42
3
DAMA Data Management Book of Knowledge. page 18.
4
DAMA Data Management Book of Knowledge. page 37.
The Minnesota Department of Transportation
Principles
Mn/DOT has adopted the following principles to better govern data. All decisions
related to data should align with the principles. More information on the
principles, including an explanation, rationale and implications for each can be
found in Appendix 1.

Data shall be managed as a state asset

Data quality fits its purpose

Data is accessible and shared as permitted

Data includes standard metadata

Data definitions are consistently used

Data management is everyone’s responsibility

Data shall not be duplicated
Figure 3.2: Mn/DOT data governance framework
Recommendation 1: The Data Governance Board shall formally adopt
the principles on behalf of Mn/DOT and incorporate them into policies,
standards and processes
Suggested strategies:
A. Adopt the data management principles at the initial Data Governance
Board meeting
B. Incorporate principles into policies, standards and processes
Chapter 3: Data Governance
43
C. Develop a communication plan to include the principles for targeted
audiences such as data coordinators, data stewards and other data
stakeholders
D. Develop a training plan to include the principles for targeted audiences
such as data coordinators and data stewards
Rationale:
Along with the vision and mission for data, the principles are the foundation to the
data governance program. Data problems or conflicts can be held up to the
principles to aid in a resolution. For example, if data is being duplicated, the Data
Governance Board can refer to the principles and determine that the data should
not be duplicated.
Policies
Policies are needed to guide the organization and data governance structure in
managing data. They are more fundamental and business critical than detailed
standards. Mn/DOT has several data-related policies in place. However, these
policies need to be reviewed, updated and enforced. Additional policies may
need to be developed to move Mn/DOT along the data management maturity
model.
Recommendation 2: Revise existing policies (e.g. stewardship,
development, data security, database recovery, data retention) and
develop additional policies needed to implement data governance at
Mn/DOT
Suggested strategies:
A. Charge a Data Stewardship Steering Committee to assess current
policies relating to data to determine their efficacy
B. Revise any policies that are obsolete, confusing or inaccurate.
C. Develop new policies that need to be implemented
D. Develop an implementation plan to include a process for accountability,
maintenance, communications and training
Rationale:
Data policies describe what to do and what not to do. As an organization
implements a formal data governance program, the informal data policies need to
be formalized and enforced. If data policies are not created and enforced data
quality and sharing issues will persist.
44
The Minnesota Department of Transportation
Standards
Similar to policies, current standards must be reviewed and enforced while new
ones must be adopted. Standards allow stewards to aid the Data Governance
Board in applying and enforcing the data policies. The Data Governance Work
Team established the standard for metadata elements which was approved by
the Business Information Council in November 2009. (See Appendix 2 for the
metadata elements standards)
Recommendation 3: Adopt or revise existing standards (e.g. metadata
elements, naming conventions, physical data modeling) and develop
additional standards needed to mature data governance at Mn/DOT
Suggested strategies:
A. Charge a Data Stewardship Steering Committee to assess current
standards relating to data to determine their efficacy
B. Revise any standards that are out dated or unused.
C. Develop new standards that need to be implemented
D. Develop an implementation plan to include a process for accountability,
maintenance, communications and training
Rationale:
Standards let data stewards know what is expected of them relating to data
quality, sharing or accessibility. Standards also enable a method for data steward
accountability—if stewards are not meeting the standards then they can be held
accountable. Standards also allow for clear communication and increased trust
relating to data increases.
Roles
Mn/DOT has tentatively established a hierarchy of roles for managing data within
the department. It is important to note that the roles do not equate into positions
or people. Once the roles are adopted, a staffing plan will identify the positions,
either new or existing, or the people who will fulfill the roles. As mentioned above,
the structure and corresponding roles are based upon the recommendations of
an independent consultant and DAMA.
All three levels are considered stewards of data at Mn/DOT. However, their
responsibilities vary depending on their level—from strategic to tactical to
operational. The three levels receive staff support from a Data Management
Coordinator. This role assists the board and participates on committees. Details
on specific responsibilities can be found in Appendix 3. Additional data
management roles also can be found in Appendix 4.
Chapter 3: Data Governance
45
Data governance board
The members of the Data Governance Board fulfill a strategic stewardship role
that typically falls within a specific line of business or business unit. Board
members are data stewards acting in an executive data steward role. Their
allegiance to their business unit is superseded by a focus on a department-wide
perspective. Each member is empowered to make decisions on behalf of the
department. Their ability to act on behalf of the department will ensure the trust
and support of the department for the decisions that are made.
Members
The board is comprised of small group of decision makers from the department,
the CIO and Data Management Coordinator.
The members representing the business are appointed by division directors for a
term of two years to succeed the previous board members whose terms are
expiring. The terms should alternate so no more than three are expiring in any
given year.
The CIO and Data Management Coordinator are permanent members.
Chair
The chair of the Data Governance Board is one of the members from the
business, elected by the other board members and considered the Chief Data
Steward. The chair is responsible for guiding the board while retaining a
department-wide perspective. He/she needs to resolve conflicts and establish
relationships with the Data Stewardship Steering Committees.
Recommendation 4: Form a Data Governance Board to replace the BIC
with members representing the divisions, the CIO and the Data
Management Coordinator
Suggested strategies:
A. Develop a staffing plan to identify positions and/or persons who take on
the Data Governance Board role
B. Review and adopt the Data Governance Board responsibilities as the
board charter
C. Develop a work plan for implementing policies, standards and processes
for data governance
46
The Minnesota Department of Transportation
Figure 3.3: Data governance roles
Rationale:
As with any new program, data governance will need top management support
and action. The board is kept small to aid in scheduling, accountability and
decision making. Larger data governance projects or initiatives that require more
people can be delegated to a data stewardship steering committee.
Data Stewardship Steering Committee(s)
One or more Data Stewardship Steering Committees are created to support the
Data Governance Board. They are tasked with drafting policies and standards for
review and approval by the Data Governance Board regarding specific initiatives,
and overseeing these sponsored initiatives. Each committee should be
composed of the Data Management Coordinator, data stewards and a data
architect, depending on the charge of the committee. Also, each committee
should be made up of six to eight members to aid in the committee’s agility and
decision-making ability.
Recommendation 5: Create the Data Stewardship Steering Committee
role as part of the larger data governance program
Suggested strategies:
A. Determine the purpose or charge for each data stewardship steering
committee
B. Identify data domain coordinators to serve on each committee
Rationale:
Although the Data Governance Board will provide overall direction for data
governance, additio nal help will be needed to research, develop and implement
policies, standards and processes. The Data Stewardship Steering Committees
will provide the organization to make the actual work happen.
Chapter 3: Data Governance
47
Figure 3.4: Relationship between data level
Data Stewards
Data Stewards are accountable for a specific type of data. They also may be data
definers, data producers or data users. The data stewardship roles are not
necessarily equivalent to a person or position. One position may fulfill one or
more roles at a time and one role may be assigned to more than one position.
There may be a particular situation where a stewardship role is a full-time
responsibility. However, in most cases, these roles are part-time.
One Data Steward should be identified to represent one or more domains of
data. In order to manage data, individual data sets need to be aggregated into
larger domains (groups, categories, etc.) and then assigned a steward. Data
Stewards are knowledge workers and business leaders recognized as subject
matter experts who are assigned accountability for the data specifications and
data quality of their assigned data domain or data set. They work closely with
their customers, peers and other stakeholders to manage their data and data
requests.
Recommendation 6: Formalize the Data Steward role as part of the data
governance program
Suggested strategies:
A. Integrate the notion of data stewardship into policies, standards and
processes
B. Define data domains, data sets and stewards needed to represent all the
data used by Mn/DOT’s products and services
C. Formally identify data stewards for core or department-wide data domains
and sets
48
The Minnesota Department of Transportation
Rationale:
Data governance will fail without a strong stewardship role. The stewards are
ultimately accountable for the quality, accuracy and timeliness of the data. Data
Stewards should also be knowledgeable enough to answer questions and
recommend improvements. They come from the business and by whom and
know how the data is used.
Data Management Coordinator
The Data Management Coordinator is the highest level coordinator with a
department-wide data perspective and full-time responsibilities for data. Besides
the CIO, the Data Management Coordinator works closely with the Chair of the
Data Governance Board to maintain the data strategy and oversee data
management projects. The coordinator role will be necessary to influence,
facilitate and advise other Mn/DOT staff on data governance issues or best
practices.
A Mn/DOT example that is analogous to the coordinator role is Mn/DOT’s Safety
Director. The Safety Director is centrally located, but has influence and is
accountable for safety department-wide. The Safety Director works with safety
peers, professionals and other stakeholders throughout the department, but
those positions do not report directly to the director. The Safety Director is
responsible for policies, standards and processes. However, he/she is not
necessarily responsible for implementation. Additionally, similar to data, safety is
the responsibility of everyone at Mn/DOT—the Safety Director is just a single
point of contact for any questions relating to safety.
Chapter 3: Data Governance
49
Figure 3.5: Relationship between data roles
Figure 3.6: Mn/DOT example of Data Coordinator and Data Steward
(Illustrative use only)
50
The Minnesota Department of Transportation
Recommendation 7: Assign the Data Management Coordinator role
within Mn/DOT.
Suggested strategies:
A. Develop a staffing plan to fill the Data Management Coordinator role.
Rationale:
A key, coordinating role is needed to oversee and shepherd the data governance
program. The role will work on data management efforts full-time and give the
program the attention it will need, especially at the onset. The coordinator will
work with all levels of stewardship and provide staff support to the board and
committees.
Processes
Several processes will be required to govern data assets. A department-wide
architecture and a business data catalog are two initial processes.
Figure 3.7: Relationship between data governance and Division Directors’
investment management.
Integration with the Division Directors’ investment
management process
While data governance is concerned with data; the Division Directors’ investment
management process (“snake”) is concerned with application development. Data
requests can be made either as part of a new application or independent when
no application change is needed. Using an analogy to the building trade may
help increase understanding between the two areas. Data governance is similar
to the building codes established by governing institutions such as the
legislature. Division directors’ investment management is similar to building the
actual structure. Data Stewards and department-wide IT architecture are the link
between the two areas — similar to planners or inspectors on a building site.
Chapter 3: Data Governance
51
Recommendation 8: Develop a process to integrate or create touch
points between data governance and Division Directors’ investment
management
Suggested strategies:
B. Incorporate data projects into the Division Director’s IT Development
Investment Plan
Rationale:
Data change requests may be made directly to the Data Governance Board or
made as part of the application development process. A new process needs to be
developed to manage data requests regardless of where the request originates.
Department IT architecture
Mn/DOT is in the beginning stages to complete a comprehensive assessment of
its information system architecture. The assessment will identify opportunities for
improving efficiencies and interoperability between existing and proposed
information systems.
Department IT architecture process requires a strong linkage to:

Department strategic planning: A successful architecture must be
aligned with the strategic plans of the organization, including the Data
Business Plan

IT portfolio management: Agency projects will be mapped to the
business function they are aimed to support. The functions are
examined to determine where sharing of services, products, and data
can take place within Mn/DOT’s architecture

Budget process: Data business strategic initiatives and projects will
help set priorities and determine investments in the architecture
Business Data Catalog
Currently, data at Mn/DOT is in many places, making it difficult to locate, gather,
use and share. A business data catalog would enable those who need data to
determine if it exists, locate it, share it, and contact the steward responsible for it.
The development of a Business Data Catalog is dependent on the
implementation of a data governance program, especially the prioritized
identification of data domains/sets and corresponding data stewards. Data
standards also need to be in place, including naming conventions and metadata
elements.
52
The Minnesota Department of Transportation
Recommendation 9: Initiate a project to implement a Business Data
Catalog
Suggested strategies:
A. Initiate an IT project to implement a Business Data Catalog using the
recommendations made by the independent consultant
B. Develop the catalog concurrently with the business intelligence project in
order to eliminate duplication of effort during the development of the
catalog iterations
C. The project will implement multiple deliverables and activities, including a
method to validate the data and implement a data management plan,
maintenance plan and security procedures. In addition, the project will
identify a tool to implement the Business Data Catalog. The data will need
to be organized and cataloged based on the data domains/sets with
responsibilities assigned to corresponding Data Stewards
Rationale:
A project is required to implement the business data catalog, since it is a multistep iterative process that can leverage processes and deployment resources
being coordinated through the business intelligence project. The business data
catalog project is an opportunity to ‘recertify’ data as the sole trusted source,
owned by a business data steward, and accessible to the department. A project
will also ensure that business requirements are gathered and the technology
meets these business requirements, while enforcing the governance framework.
Conclusion
Implementing data governance is a journey, not a one-time project. The journey
has been in process for many years and now is the time to take a larger step
forward. The implementation of the current data governance framework will not
be perfect, but it needs to begin if data is truly to be treated as an asset at
Mn/DOT.
Engagement among all business data stewards will be required to strengthen
data governance at Mn/DOT. Strong, enforced roles, policies, standards and
processes will take Mn/DOT further on the maturity model and ensure the data
principles become a living part of Mn/DOT’s culture.
Chapter 3: Data Governance
53
54
The Minnesota Department of Transportation
Chapter 4: Geographic Information
Systems Introduction
Geographic Information Systems provide powerful spatial data analysis tools for
transportation planning, project development, asset management and
maintenance operations. As part of the development of the Data Business Plan, a
revision of the department’s GIS Strategic Plan was implemented. This chapter
summarizes the new GIS Strategic Plan and provides background information
and a series of recommendations for strengthening GIS use at Mn/DOT.
Background
Mn/DOT has always been a leader in the development and deployment of new
technologies, including GIS. While the department has made strategic
investments to support GIS, these have often been associated with the
development and deployment of individual GIS-related projects. This project
based deployment process has lead to a mature technology environment, which
has only begun to realize its full potential as a business tool supporting business
decision making. However, the result has been inconsistent use and deployment
of GIS initiatives across the department as a whole. Large databases of
geospatial information have evolved that could be applied more broadly in an
effort to align GIS technology and business processes with department-wide
priorities. Overall, there are opportunities to more fully optimize GIS and build
stronger ties between geospatial data and business decision making.
GIS industry directions and trends
GIS is rapidly growing and transforming. It began as a system that was primarily
workstation-based and isolated from other business systems. It is now closely
linked to the rapid growth of other information technology industry trends and a
maturing, yet dynamic industry. Some of these industry trends will play an
important role in easing and facilitating the introduction of a department-wide GIS
for Mn/DOT. Examples include:
1. Improved usability of GIS – In recent years, GIS has become easier to
use, more intuitive, more analytical and more embedded with a variety of
technologies. Thus, it has become much more usable to a broader set of
disciplines as well as business processes.
2. Department-wide integration – Increasingly, GIS is being valued as
integrating technology and core technology that should be available to all
users. As a result, GIS is assuming more of a department-wide role in
organizations.
The Minnesota Department of Transportation
55
3. GIS on the Web – GIS will continue to become more web-based.
Improvements in Internet speed, cost and availability have brought about
innovations in website technologies. These technologies are improving
the usability and response times of Internet sites and are an attempt to
bring browsing more in line with the desktop experience (Mitchell, 2006).
4. GIS data in relational database management systems – As the
industry changes to more open systems, the relational database
management system has emerged as the preferred way to store GIS
information, primarily because of the open architecture standardization
and ability to integrate with other databases.
5. Open access to GIS data – With the proliferation of personal computers,
use of the Internet and standardization of GIS data formats, access to
GIS data has become much easier and widespread. Many governments
and private businesses post data on websites for download and
consumption, either for a fee or free of charge. Partners are working
together to make more data available for sharing across organizations.
6. Emphasis on corporate management of GIS – Increasingly,
organizations are moving toward a corporate management approach to
GIS. This kind of emphasis requires a business-driven, coordinated
oversight with responsibility for software and infrastructure support in a
department that is neutral, such as an IT department.
7. Mash-ups – There is a demand from business and government to
provide services that can be combined into mash-ups. A mash-up is a
website or application that uses content from more than one source, often
public data, to create a completely new service. Mash-ups are
revolutionizing Web development and will influence the way maps and
business information can be published on the Web, especially involving
third-party vendors.
8. Mobile GIS – Wireless technologies combined with Web-enabled GIS are
allowing business applications and work flow to become more connected
and mobile. This is allowing spatial data to be moved into the field and
used in many ways, such as feature location and capture (e.g. assets),
field editing of data, workflow management and routing.
9. Search and discovery – Spatial technology provides another method to
search data and content. Spatial selection of map features or selection of
geographies allows users to gain quick access to content. The ability to
share information though map selection provides better access to
information and a greater capacity to interact with business and public
customers. This is a true e-government opportunity.
10. Broad public acceptance and knowledge – GIS has been a driving
force behind much of the mainstreaming of Web-based mapping found
today on the Internet. Websites like MapQuest and Google Earth deliver
GIS functionality and have raised public awareness and acceptance of
finding information via a mapping interface. Not only are map interfaces
56
Chapter 4: Geographic Information Systems Introduction
becoming more accepted for obtaining information, the public’s skill level
has increased.
A tool in the toolbox
Mn/DOT’s Data Business Plan focuses on data gaps and needs, and
strengthening how data and information are managed to support decision
making. GIS is a tool in the toolbox that will greatly enhance the department’s
ability to access and use data to respond to inquiries and look at data and
information in new ways. This will help functional areas be more responsive and
effective in their efforts to manage transportation infrastructure in the State of
Minnesota.
As the GIS directions and trends indicate, ease of use, department-wide
integration, web-based technologies, open access, mash-ups and mobile
computing will all lead to broader use, shared data, and transparency of data to
answer questions and help plan effective and efficient investments for
transportation in Minnesota. As GIS technology is deployed department-wide, we
will see significant changes in the way we conduct business and business
decision making. These changes will occur as a result of data being looked at in
new ways, on a broader base, and with people more knowledgeable about data
that will support a data driven point of view.
The following recommendations are offered to more fully optimize the use of GIS
tools, technologies and data at Mn/DOT.
Identify core Geographic Information System
spatial data needs
Mn/DOT currently maintains numerous GIS themes as core spatial data.
However, more work is needed to strategically examine the department and
identify the core spatial data needs and priorities necessary to fulfill Mn/DOT’s
mission and drive primary business processes and performance metrics.
Recommendation 1: Undertake a formal assessment of currently
available GIS data and determine what is essential or core data, and
where there are gaps and needs
Suggested strategies:
A. Identify core GIS data sets and stewards of those data sets
B. Accelerate efforts to make core GIS data available to users throughout
the department
The Minnesota Department of Transportation
57
C. Develop a communication plan to share information on the availability of
GIS core data broadly with users throughout the department
D. Develop new or revise existing processes for developing GIS standards
for data collection and management
E. Create common standards, processes and tools for defining, sharing, and
accessing core spatial data
Rationale:
Mn/DOT’s mission to “provide the highest quality, dependable multi-modal
transportation system through ingenuity, integrity, alliance and accountability” will
drive data needs over a wide range of data domains. With an eye toward data
governance and our first strategic goal of “establishing and promoting GIS
standards and best practices within the department,” there is a need to review
currently available GIS themes to determine whether they are or should remain
core spatial data. Many of these data were developed to support a project-based
GIS environment, and while many are core spatial data, some may not be. In
addition, there may be priority core spatial data gaps and needs that will need to
be addressed to promote more effective and efficient business decisions. The
following recommendation is proposed to assist the department in identifying
core GIS spatial data needs.
Provide strategic direction for GIS to address
business needs for geospatial data
The department faces many challenges, including aging infrastructure,
environmental concerns, diversity and demographics, rapid change and mobility
concerns and fiscal responsibility. These are our critical issues, and they are data
driven challenges. Most data can be linked spatially and many of these issues
are clearly spatial data opportunities. A strategically driven department-wide GIS
would support questions like:
1.
2.
3.
4.
5.
Where is aging infrastructure failing to meet targets?
Where are wetlands being removed and where are they being replaced?
What are regional demographics by area?
Where is congestion occurring? What are alternative routes?
How does fiscal planning by regional inputs, compared to age of
infrastructure?
6. Where do safety improvements and pedestrian considerations need to be
made?
7. What areas are underserved by transit?
These are all examples of how a department-wide framework for GIS could be
utilized to respond to critical issues and assist in business decision making that
supports the department’s mission, vision and strategic directions.
To evaluate and recommend development of applications and geospatial data
needs in support of this effort, we will require a collaborative process with input
58
Chapter 4: Geographic Information Systems Introduction
from business and functional areas throughout the department. The following
recommendation addresses the need for a committee, team or entity to guide,
steer and direct future investments in geospatial data and architecture.
Recommendation 2: Establish an entity to recommend and steer the
development and review of GIS-related projects, initiatives, and
investments to the division directors’ “Snake” process
Suggested strategies:
Establish a GIS steering team to guide and direct the significant investment the
department has in GIS architecture to support a broader business decisionmaking purpose from the current project driven architecture we currently have.
A. There are needs for business decision support applications that will need
to be developed.
B. There are geospatial data that will need to be evaluated for redundancy,
shared use, and future needs.
C. The process of this review and direction will feed the Division Directors
“snake” process for GIS related projects and data needs.
The GIS Steering Team could coordinate geospatial data needs and existing
geospatial data under the direction of the Data Governance Board in cooperation
with the Data Domain Stewards.
The GIS steering team should guide the evaluation of existing data, technologies
and resources that could be leveraged easily to respond to immediate needs of a
broad set of potential users to deliver “low hanging fruit” opportunities that exist.
Focus on areas that bring GIS data and mapping to the desktop of users.
Additionally, determine what capability exists to provide remote access to a data
platform for planning and presentation purposes.
Rationale:
Although GIS technology is mature within the organization, on a project basis,
the broader use of GIS as a business decision support tool is a new strategic
effort. Providing a strategic focus to target GIS investments to priority business
decisions will improve transparency, accountability and efficiency, but it will need
guidance and direction that a steering team can offer.
To further the development of GIS as a business decision support tool, the
department should leverage existing data, technology and resources to respond
to a broad base of customers that can use GIS to improve business decision
processes quickly. Having a steering committee in place can promote the value
of GIS for employees and customers, and generate new ideas for taking
advantage of GIS to better meet business needs. Having a steering team
leadership structure can also help drive future GIS development and investment.
This approach would feature low-cost high-benefit uses like desktop and remote
mapping capability. Some examples to consider:
The Minnesota Department of Transportation
59



Mapping on the fly at a remote public meeting location to illustrate area
impacts, locations, or other project features
Preparing presentation materials for snow and ice response
Drainage area maps for discussion at a project meeting, or for inclusion in
to a scoping document
All of these could be spatial tools that would service employees and customers
getting good business information in front of decision makers quickly and
efficiently.
Strengthen GIS business support
There are many opportunities throughout the department for utilizing GIS to map
data for analysis and decision making. However, not all districts or offices have
immediate access to GIS professionals. The following recommendation
addresses the need to strengthen GIS business support for all areas across the
department.
Recommendation 3: Create a GIS Business Support Unit consisting of
GIS professionals to assist users with the production of maps and
analytical needs beyond desktop business support tools
Suggested strategies:
A. Create a GIS Business Support Unit consisting of GIS professionals who
would be focused on customer production needs
B. Provide professional production services above those offered on the
user’s desktop application, in response to questions asked by employees,
partners and stakeholders
C. Provide knowledge of GIS databases and data quality to help complete
analytical work in response to questions asked by employees, partners
and stakeholders
D. Ensure that the placement in the organization of the GIS Business
Support Unit would allow services across the entire department without
regard to boundaries or silos
E. Establish an ancillary committee structure to support evaluation of various
pilot projects, initiatives or further development of existing applications—
allow the GIS Business Support Unit to provide coordination efforts and
advisory input on user and customer data needs they see in performance
of their duties. The GIS business support unit should also coordinate
architecture issues from a user’s perspective with the office of Information
& Technology Services.
60
Chapter 4: Geographic Information Systems Introduction
Rationale:
From time to time, and more frequently as users come to expect this type of
business decision support, there is a need to get more skilled GIS response to
questions or analysis requiring geospatial data. Those times should be supported
by GIS professionals shared across the department. In general, a GIS Business
Support Unit should be located closest to its customers and have capability to
complete analytical responses and production needs for those customers. The
GIS Business Support Unit
should be staffed with GIS
professionals capable of these
functions. The unit would also
assist users in crafting requests
for improvements in GIS to help
meet business processes and
future needs. Metro District’s GIS
Unit would be a model to consider
for this unit, but with a breath of
service to all the districts and
other divisions. The GIS Business
Support Unit would have to work
closely with the OI&TS EGIS Unit
to coordinate business
architecture and data needs.
OI&TS roles and responsibilities would have to be reviewed to ensure this
coordination is understood and functional between the units.
Align data governance and GIS
Geographic Information Systems are by nature data intensive applications that
will benefit from strengthened data governance effort. It is imperative that
strategies implemented to provide GIS services to Minnesota and Mn/DOT are in
alignment with the data governance principles outlined in Chapter 3 of this plan.
The following recommendations will ensure that GIS efforts are aligned with
adopted Mn/DOT data governance principles.
Principle 1: Data shall be managed as a state asset
Data that are effectively managed as state assets will likely be collected once
and used many times. They are often centrally managed and there may be a
hierarchy of offices, committees and users to work through to prevent and correct
errors in data. It will be important to facilitate processes that improve data quality
and integrity, as well as respond to and address flawed processes that produce
data errors. Given the large user base of GIS data, a periodic forum with
department-wide representation is needed to decide on process corrections and
data issues. The scope of such an endeavor and the cost of collecting numerous
people in one place make this a difficult proposal to achieve.
The Minnesota Department of Transportation
61
Recommendation 4: Identify and implement effective methods for
periodically convening spatial Data Stewards and users to get input on
opportunities and imperfect processes and share information on
innovations and data concerns.
Suggested strategies:
A. Create processes to evaluate geospatial data from a Data Steward point
of view
B. Create processes to evaluate geospatial data from a broader user point of
view—the format for this effort could be modeled after the E-magination
JAM initiative recently completed by Mn/DOT
C. The GIS Steering Team would use these input processes to help guide
and direct the future development of GIS, geospatial tools and geospatial
data
Rationale:
Any GIS application is data intensive and the outcome is only as good as the
data input. With the breadth of current data and the potential expansion of data
that a broadening of purpose beyond specific projects may create, there is a
need to reach out to users and Data Stewards on a regular periodic basis to
ensure we are meeting business needs. The E-JAM effort proved that input could
be obtained from a broad array of people and successfully turned into reality. It is
believed that this could work as a process to ensure that we manage the
geospatial data as a state asset serving state resources effectively.
Principle 2: Data quality fits its purpose
To be fit for its purpose, GIS data must be of sufficient accuracy and meet
business needs for which it is intended— integrity should be proportional to its
use and cost of collection and maintenance. GIS data has a unique relationship
to its accuracy depending upon its intended use. Much of Mn/DOT’s GIS data is
at 1:24,000 resolution, the same as a USGS quadrangle map. While suitable for
planning activities, a much higher resolution would be required to do parcel
mapping, design-level analysis or asset management. Expanding the scale of the
mapping used by Mn/DOT is an expensive effort to undertake. It must be planned
and deployed over time so it can be affordable and effective.
62
Chapter 4: Geographic Information Systems Introduction
Figure 4.1: Vision, goals, objectives and strategies
Vision
Enhance the business decision-making process through the availability of a high quality
Geographic Information System.
Goals
1. Governance
2. Guidance
3. Sustainability
Establish and promote
GIS standards and best
practices within the
department
Improve the GIS
Deploy resources to
knowledge base within enable efficient GIS
the department
integration and
growth
4. Data Services
and Support
Deploy enterprise
resources to meet
business needs for
data access and
support
Objectives
 Establish and
promote standard
methods and
procedures for GIS
application
development
 Establish and
promote standards
and procedures for
data collection,
development, and
maintenance
 Design and
implement
department-wide GIS
architecture
 Define core set of GIS
data and
infrastructure
 Establish
mechanisms for GIS
idea sharing,
discussions,
information and user
group networks in
order to grow GIS
knowledge base
 Establish processes
to review and
support
development of
business processes
to enable
integration and
efficiency
 Educate all levels of
users on current and
potential use of GIS
 Develop an ongoing
GIS support system
to enable efficient
use of departmentwide GIS resources
 Provide GIS training
to varied audiences
to increase the skill
level of all levels of
GIS users
 Develop an
Enterprise GIS
model that provides
structure for GIS
infrastructure (i.e.
governance,
technology) and
GIS business
support (i.e.
production, data
development) roles
 Establish a
leadership structure
with roles and
responsibilities
The Minnesota Department of Transportation
 Establish efficient
and reliable data
access, within and
outside the
Department
 Provide centrally
managed structure
to support creation
and maintenance of
spatial data
 Establish and
populate a central
data
catalog/metadata
repository
 Establish a
review/approval
process to manage
data development
requests from an
enterprise
perspective
 Establish a support
structure to assist
business areas in
using GIS data and
technology to meet
production needs
63
Recommendation 5: Develop processes to manage GIS technology
improvements, GIS data investment and data integrity/accuracy
decisions to ensure they are balanced against the business need for
which they are intended
Suggested strategies:
A. Develop methodologies to ensure future investments in data and
architecture are based on return on investment and assist with business
decision-making processes
B. Identify opportunities and actions to achieve GIS Strategic Plan objectives
C. Recommend training and/or other resource or process changes that can
help optimize the use of GIS
D. Develop accuracy standards that fit business needs for geospatial data,
including assets, events and boundaries
Rationale:
Much of Mn/DOT’s GIS data is at 1:24,000 scales, the same as a USGS
quadrangle map. While suitable for planning activities, a much higher resolution
would be required to do parcel mapping, design-level analysis or utility location.
Expanding the scale of the mapping used by Mn/DOT is an expensive effort to
undertake. It must be planned and deployed over time so it can be affordable and
effective. This would include guiding tactical investments and assisting in the
implementation and updating of the GIS Strategic Plan and GIS Work Plan. This
would be a key leadership role for the committee, team or entity that is put in
place to guide future development and manage the GIS effort. The focus should
be based on business needs and business decision support requirements.
Principle 3: Data is accessible and shared as permitted
GIS data must be accessible to consumers, as well as across department
functions, districts, offices and to external partners to be effective and efficient in
delivering the full capability of GIS technology. Users, partners and stakeholders
must have access to GIS data in accordance with applicable laws and
regulations in order to maximize the decision-making processes in product and
service delivery. Sharing GIS data with many partners will create a unique set of
issues regarding data quality, integrity and accessibility. For GIS to attain its full
value, it must be shared and accessible.
64
Chapter 4: Geographic Information Systems Introduction
Recommendation 6: Implement geospatial governance formats and
protocols and geospatial technology that allow for sharing of geospatial
data with partners and stakeholders to achieve necessary accessibility
and ensure data quality, consistency and integrity
Suggested strategies:
A. Build trust and transparency in the department as a trusted source of
information by sharing geospatial data that is consistent and easily
integrated—develop accessibility guidelines to ensure internal geospatial
data quality and integrity are preserved
B. Use geospatial data that has applicable function for state purposes from
partners and stakeholders— Geospatial data standards and data
definitions need to be established with partners so sharing can be
optimized
Rationale:
Sharing geospatial data will ensure Mn/DOT is seen as a trusted source of
information and its partners will openly accept and share data, while Mn/DOT
saves resources by not duplicating data that may be available from partners and
stakeholders.
The recommendations involve much consideration for data sharing with internal
and external partners and stakeholders. The principle of data sharing will
continually conflict with the principle of data security. Under no circumstances will
a data sharing principle cause confidential or private data to be compromised.
The department must be vigilant to safeguard private and confidential data, while
being open to sharing data that is valuable to its partners and stakeholders.
Principle 4: Data definitions are consistently used
Sharing GIS data is best accomplished when the data is uniquely and accurately
identified. Data meaning and clarity are enforced through data element definitions
that consist of a written description of what the data element is and how it is
used, its domain values and its physical format. Data element names are
structured with consistent format for content. Data governance practice will
ensure data definitions are consistently used and roles and responsibilities will be
defined. This is important for GIS data because of the high level of data sharing
and accessibility we hope to achieve. Data governance practices must be
coordinated with partners and stakeholders so that we can share data.
The Minnesota Department of Transportation
65
Strategic planning for GIS
Mn/DOT’s Strategic Plan for GIS serves as a guide to better leverage GIS
investments and ensure future priorities for GIS technology and business
practices are aligned with department-wide priorities. The plan describes the
vision, goals and objectives for the long-range view of a department-wide GIS.
The anticipated outcomes of the GIS Strategic Plan are:
1. Standard methods and processes for GIS applications and data at all
levels including performance measures and return on investment
2. Optimized and enhanced department-wide GIS architecture
3. Resources and guidance for communication, education, training and
business support
4. Clear organizational structure with roles and responsibilities defined to
support GIS activities that add value to the delivery of Mn/DOT’s products
and services
5. A clearly defined set of core GIS products and services, as well as
(transparent) methods for accessing them
6. Compliance with departmental data governance: principles, policies,
standards, roles and processes
Leadership to guide and support spatial enablement,
integration, and sharing of data and technology
Figure 4.1 outlines the vision, goals, objectives and strategies outlined in the
department’s newly revised GIS Strategic Plan.
Within the GIS Strategic Plan, there are multiple strategic initiatives for each
objective that will be considered in the deployment of a department-wide GIS.
Rationale and implications are provided to help define issues when these
initiatives move forward. For complete details, please refer the GIS Strategic
Plan.
The deployment of a department-wide GIS will be tactically driven by a biennial
GIS Work Plan. The first work plan will be developed by December 2010 and
direct investments for the balance of the 2010-2011 biennium in GIS. The plan
will be developed by the GIS Work Group that developed the strategic plan.
Subsequent work plans will be developed by the GIS Steering Team.
66
Chapter 4: Geographic Information Systems Introduction
Recommendation 7: Update the GIS Strategic Plan approximately every
five years, or as the technology evolves to require updates.
Furthermore, a GIS Work Plan should be created every biennium to
specifically direct tactical deployment and budget investments in
deploying a department-wide GIS.
Suggested strategies:
A. The technology that supports a geographical information system has an
estimated lifecycle of about five years. Therefore, it would be prudent to
plan for development at a strategic level for twice that lifecycle period as a
long-range planning cycle
B. The resources that drive investments in the technology and geospatial
data are driven on a biennial time period. Therefore, it would be prudent
to plan for tactic development on a biennial basis
C. While these documents can exist on their own, it makes sense to have
the investments in the work plan driven by the strategic initiatives of the
strategic plan. Building a strong connection between the two plans will
ensure effective deployment and response for the future of the
department-wide GIS
Rationale:
To achieve the vision of the GIS Strategic Plan, we will need to have focused
leadership and strong direction. By periodically revisiting these plans, we will
provide the direction as the needs change over time. Technology changes quickly
and our data needs will evolve quickly over time. It is essential that the
department provide a leadership team that can respond to that change just as
quickly.
Conclusion
This chapter of the Data Business Plan provides background information and
recommendations for optimizing the use of GIS in the department to support
business decisions and providing more strategic direction and governance to GIS
investments, development and deployment efforts. The content of the chapter
follows the goals and objectives outlined in the department’s recently revised GIS
Strategic Plan.
In the Mn/DOT GIS Strategic Plan, beginning with the problem statement, it was
noted that clear strategic direction helps establish clear organizational structures
with roles and responsibilities designed to support GIS activities and add value to
the delivery of Mn/DOT products and services. Implicit in the GIS
recommendations outlined in this chapter are organizational changes for
strengthening how the department guides, directs and aligns GIS to support the
business. In a large organization, when someone refers to organizational
The Minnesota Department of Transportation
67
change, people gravitate immediately to the organization chart. The
recommendations in this chapter suggest that decision makers resist that
temptation and focus on the larger picture of what ancillary group structure and
group interactions are necessary to make the GIS Strategic Plan goals and
objectives functional. GIS is one tool in the toolbox and is dependent on data.
Data governance group structures will have a significant role and responsibility
that will overlap with GIS and the deployment of a department-wide GI.
68
Chapter 4: Geographic Information Systems Introduction
Chapter 5: Conclusion
The completion of this first Mn/DOT Data Business Plan is the culmination of
more than two years of hard work and numerous discussions about data and
information challenges, issues and opportunities. Personnel from throughout the
department were involved in helping with surveys, focus groups, meetings and
committee assignments. In the end, data business planning provided an
extremely effective process for identifying opportunities to strengthen Mn/DOT
data and information programs.
Strengthening the decision support process by data that are reliable and
consistent is tied to best investment practices that are sustainable. By instituting
a best practice approach to data governance and implementing processes that
are repeatable and based on a solid framework, the strategic approach to using
technologies such as GIS will carry a message of transparency with the agency
as well as the traveling public. By increasing data availability, the gaps and
needs will become evident and can be addressed. The Data Governance Board,
along with continued work of the Stewardship Council will provide for strong data
to support agency investment priorities. The resources invested in the framework
support structure and strong governance will return positively with data of greater
reliability, and provide quick response to decision-makers via integrated and
easily assessable data.
Data business planning results lay out an ambitious but achievable framework of
recommendations and strategies for 2011-2012.
Plan recommendations and strategies provide a solid starting point for enhancing
data and GIS to support key business decisions and traveler safety, infrastructure
preservation and mobility performance outcomes. Plan recommendations and
strategies also lay the groundwork for managing data and information more
effectively and for creating a more mature culture for data governance.
Implementing plan recommendations will require continued work, resources and
a strong commitment to manage data and information as department assets. For
example:
1. The infrastructure preservation recommendations set the stage for
implementing an organizational approach to asset management and for
addressing critical transportation infrastructure data gaps and needs.
2. Traveler safety recommendations cite the need for better data on local
road characteristics and more enhanced safety data analysis tools.
3. The mobility recommendations identify the need for research and
resources to collect potentially new data to address increasing interest in
multimodal accessibility, reliability and person throughput questions.
4. The financial data recommendations address the need for enhanced
information on life-cycle costs, return on investments and data for
evaluating service delivery options.
The Minnesota Department of Transportation
69
5. Business intelligence recommendations highlight the value of departmentwide solutions for improving data availability, integration and analytical
capabilities.
6. Enterprise architecture recommendations provide an opportunity to
strategically look at how all information systems might fit together to
reduce data redundancies and create operational efficiencies.
7. The data governance recommendations lay out a comprehensive series
of steps for clarifying data roles and responsibilities and for setting
standards and policies to reduce redundancies and promote data quality
and reliability. They recommend developing a data catalogue and a
thorough assessment of department-wide information system architecture
to identify opportunities for integration to reduce redundancies and
promote efficiencies.
8. The GIS recommendations set the stage for business process, data
governance and organizational changes to fully achieve desired
objectives.
Over time, the recommendations and strategies included in this plan will lead to a
future where data and information are managed as assets. Together with
organizational structures, processes, policies and standards, those data and
information assets will support overall multimodal policy, planning, program and
project investment decisions.
The Business Information Council that guided business planning efforts will
disassemble when the Data Business Plan is approved by the department’s
Stewardship Council. The Data Business Plan recommends that a new
permanent Data Governance Board be created to lead the implementation of
plan recommendations and provide oversight for future data business planning
efforts.
70
Chapter 5: Conclusion
Appendix 1: BIC-GIS Members
BIC-GIS Work Team:
GIS Strategic Plan Revision Participants:
Elizabeth Benjamin
Lee Berget, Chair
Lisa Bingham
Peter Buchen
Glen Ellis
Gary Fried
Brian Gage
Joella Givens
Cory Johnson
Rocky Haider
Kathy Hofstedt
Rick Kostohryz
Matt Koukol
Jonette Kreideweis
Mike Leegard
Susan Lodahl
Ernest Lloyd
Thomas Martin
Robert Miller
Rick Morey
Tim Quinn, Chair
Mike Reynolds
Dan Ross
Mary Safgren
Mike Schadegg
Tim Spencer
Andy Trcka (Staff)
Susan Walto (Staff)
Paul Weinberger
Susan Zarling
Steering Team:
Goal 2 (Guidance)
Lee Berget
Tim Quinn
Jonette Kreideweis
Dan Ross
Kathy Hofsted
Susan Walto (staff)
Andy Trcka (staff)
Joella Givens
Glen Ellis
Sue Zarling
Jesse Pearson
Andy Trcka
Lisa Bingham
Goal 3 (Sustainability)
Edit Team:
Matt Koukol
Susan Walto
Andy Trcka
Brian Gage
Paul Weinberger
Peter Morey
Goal 1 (Governance):
Thomas Martin
Ernest Lloyd
Susan Walto
Rick Morey
Peter Dahlberg
Ryan Wilson
Charlie McCarty
Peter Morey
Dan Ross
Rocky Haider
Brian Gage
Gary Fried
Liesa Miller
Goal 4 (Data Service &
Support)
Mary Safgren
Paul Weinberger
Joella Givens
Matt Koukol
Mike Reynolds
Adam Julson
The Minnesota Department of Transportation
71
Mn/DOT Business Information Council
Council Members and Staff
Name
Office/District
BIC Role
Lee Berget
District 4 - Detroit Lakes
Member
Todd Broadwell
District 8 - Willmar
Member
Robert Brown
Land Management
Member
Jim Close
Information & Technology Services
Staff
Ginny Crowson
External Partnering
Member
Paul Czech
Metro District
Member
Nancy Daubenberger
Bridge
Member
Sue Dwight
Financial Management
Member
Glen Ellis
Metro District
Member
Judy Ellison
Transit
Member
Beverly Farraher
Metro District
Member
Sue Groth
Traffic, Safety & Technology
Member
Tim Henkel
Modal Planning & Program Management
Division
Chair
Kathy Hofstedt
Information & Technology Services
Member/ Staff
Cassandra Isackson
Traffic, Safety & Technology
Member
Steven Kirsch
District 6 - Rochester
Member
Rick Kjonaas
State Aid
Member
Matt Koukol
Transportation Data & Analysis
Staff
Jonette Kreideweis
Transportation Data & Analysis
Member/ Staff
Duane Leurquin
Investment Management
Member
Sue Lodahl
Maintenance
Member
Steve Lund
Maintenance
Member
Mark Nelson
Investment Management
Member
Frank Pafko
Environmental Services
Member
Tim Quinn
Metro District
Member
Bill Roen
Financial Management
Member/ Staff
Keith Shannon
Materials & Road Research
Member
72
Appendix 1: BIC–GIS Members
Tim Spencer
Freight & Commercial Vehicle Ops
Member
Sue Stein
Administration
Member
Linda Taylor
Policy, Analysis, Research & Innovation
Member
Andy Trcka
Transportation Data & Analysis
Staff
Pam Tschida
Employee & Corporate Services Division
Member
Steve Voss
District 3 - Baxter
Member
Susan Walto
Transportation Data & Analysis
Staff
Joel Williams
Construction & Innovative Contracting
Member
The Minnesota Department of Transportation
73
74
Appendix 1: BIC–GIS Members
Appendix 2: Summary of Survey Results
Response Key
Essential = # of respondents that declared this data type is essential out of the 120
respondents who claimed Infrastructure Preservation is their primary objective.
Fully = % of respondents that declared this data type is essential, claimed Infrastructure
Preservation is their primary objective, and thought their needs are being fully met.
Partially = % of respondents that declared this data type is essential, claimed
Infrastructure Preservation is their primary objective, and thought their needs are being
partially met.
Does Not = % of respondents that declared this data type is essential, claimed
Infrastructure Preservation is their primary objective, and thought their needs are not
being met.
NA/Don’t Know = % of respondents that declared this data type is essential, claimed
Infrastructure Preservation is their primary objective, and thought their needs are not
applicable or didn’t know.
Total - Not Fully = % of respondents that declared this data type is essential, claimed
Infrastructure Preservation is their primary objective, and thought their needs are being
partially met or not being met.
# of Responses = Number of responses used to calculate the average rating for
Accessibility, Accuracy, Completeness, Credibility, and Timeliness.
The Minnesota Department of Transportation
75
Preservation Business Emphasis Area
Data Type
Essential
Fully
Partially
Does Not
NA/ Don't Know
Total - Not Fully
Aeronautics Infrastructure
5
20%
80%
0%
0%
80%
Hydraulics Infrastructure
45
18%
73%
2%
7%
76%
Hydraulics Operation
32
22%
66%
3%
9%
69%
Signs Infrastructure
28
32%
68%
0%
0%
68%
Signs Operation
18
33%
61%
6%
0%
67%
Aeronautics Operation
3
33%
67%
0%
0%
67%
Rail Operation
6
17%
50%
17%
17%
67%
Financial
53
28%
64%
2%
6%
66%
Rail Infrastructure
14
36%
57%
7%
0%
64%
Other Road Infrastructure Condition
43
33%
56%
7%
5%
63%
Economic
16
38%
63%
0%
0%
63%
Signals and Lighting Operation
12
42%
50%
8%
0%
58%
Human Resources
45
38%
58%
0%
4%
58%
Facilities Infrastructure
28
21%
50%
7%
21%
57%
Surveying/Mapping
49
43%
57%
0%
0%
57%
Facilities Operation
23
30%
52%
4%
13%
57%
Demographic
20
45%
55%
0%
0%
55%
Planned Work
73
34%
52%
1%
12%
53%
Signals and Lighting Infrastructure
23
48%
48%
4%
0%
52%
Traffic
55
45%
47%
4%
4%
51%
Transit Operation
6
50%
50%
0%
0%
50%
Other Road Infrastructure Operation 31
45%
48%
0%
6%
48%
Fleet Operation
25
52%
48%
0%
0%
48%
Roadway Intersection
29
48%
38%
7%
7%
45%
Fleet Condition
27
56%
44%
0%
0%
44%
Construction Plans
68
53%
41%
3%
3%
44%
Environmental
41
41%
39%
5%
15%
44%
Roadway Maintenance
39
54%
36%
8%
3%
44%
Transit Infrastructure
12
50%
42%
0%
8%
42%
76
Appendix 2: Summary of Survey Results
Preservation Business Emphasis Area
Data Type
Accessible
Accurate
Complete
Credible
Timely
# of Responses
Aeronautics Infrastructure
2.75
2.75
2.50
2.75
2.50
4
Hydraulics Infrastructure
2.77
2.69
2.38
2.87
2.69
38
Hydraulics Operation
2.60
2.68
2.32
2.76
2.54
25
Signs Infrastructure
2.67
2.69
2.38
2.80
2.78
25
Signs Operation
2.53
2.73
2.40
2.80
2.73
15
Aeronautics Operation
2.67
2.33
2.33
2.33
2.67
3
Rail Operation
2.50
2.50
2.50
2.67
2.60
6
Financial
2.63
2.76
2.55
2.76
2.55
41
Rail Infrastructure
2.58
2.73
2.27
2.82
2.78
11
Other Road Infrastructure Condition
2.78
2.83
2.67
2.81
2.79
36
Economic
2.53
2.73
2.47
2.71
2.27
14
Signals and Lighting Operation
2.80
2.90
2.90
2.90
2.90
10
Human Resources
2.78
2.97
2.85
2.88
2.79
34
Facilities Infrastructure
2.60
2.78
2.61
2.78
2.76
18
Surveying/Mapping
2.95
3.15
2.78
3.10
2.74
39
Facilities Operation
2.50
2.80
2.67
2.80
2.86
15
Demographic
2.89
3.00
2.61
3.00
2.50
17
Planned Work
2.81
2.61
2.56
2.61
2.73
56
Signals and Lighting Infrastructure
2.73
2.77
2.55
2.81
2.70
21
Traffic
3.04
2.84
2.69
2.91
2.94
43
Transit Operation
3.00
3.00
2.80
3.00
2.80
5
Other Road Infrastructure Operation 2.83
2.96
2.83
2.92
2.83
24
Fleet Operation
2.95
3.00
2.90
2.95
3.10
20
Roadway Intersection
2.70
2.95
2.73
2.82
2.67
21
Fleet Condition
2.96
3.00
2.96
3.00
3.09
23
Construction Plans
2.95
2.92
2.67
2.95
2.96
62
Environmental
2.69
2.92
2.60
2.92
2.68
25
Roadway Maintenance
N/A
N/A
N/A
N/A
N/A
N/A
Transit Infrastructure
2.67
2.92
2.58
2.82
2.82
12
The Minnesota Department of Transportation
77
Mobility Business Emphasis Area
Data Type
Essential
Fully
Partially
Does Not
NA/ Don't Know
Total - Not Fully
Hydraulics Infrastructure
15
7%
67%
13%
13%
80%
Hydraulics Operation
10
20%
70%
10%
0%
80%
Roadway Intersection
19
26%
68%
5%
0%
74%
Economic
18
28%
67%
6%
0%
72%
Rail Operation
10
10%
60%
10%
20%
70%
Demographic
20
30%
65%
5%
0%
70%
Signals and Lighting Infrastructure
13
31%
69%
0%
0%
69%
Other Road Infrastructure Operation 18
33%
61%
6%
0%
67%
Financial
25
36%
64%
0%
0%
64%
Facilities Infrastructure
11
18%
55%
9%
18%
64%
Aeronautics Infrastructure
5
40%
60%
0%
0%
60%
Roadway Centerline
22
41%
59%
0%
0%
59%
Surveying/Mapping
22
41%
55%
5%
0%
59%
Transit Infrastructure
17
35%
47%
12%
6%
59%
Traffic
29
34%
59%
0%
7%
59%
Rail Infrastructure
12
42%
50%
8%
0%
58%
Crash
24
42%
50%
8%
0%
58%
Fleet Operation
9
44%
56%
0%
0%
56%
Signs Infrastructure
11
45%
55%
0%
0%
55%
Planned Work
33
33%
52%
0%
15%
52%
Fleet Condition
10
50%
50%
0%
0%
50%
Other Road Infrastructure Condition
12
50%
50%
0%
0%
50%
Signs Operation
6
50%
50%
0%
0%
50%
Transit Operation
10
50%
40%
10%
0%
50%
Environmental
23
48%
48%
0%
4%
48%
Human Resources
17
53%
47%
0%
0%
47%
Roadway Maintenance
9
56%
33%
11%
0%
44%
Signals and Lighting Operation
7
43%
43%
0%
14%
43%
Bridge Operation
5
60%
40%
0%
0%
40%
Pavement Condition
20
60%
35%
5%
0%
40%
Weather
10
60%
20%
20%
0%
40%
Construction Plans
28
57%
39%
0%
4%
39%
Bridge Infrastructure
18
56%
39%
0%
6%
39%
Aeronautics Operation
3
33%
33%
0%
33%
33%
Facilities Operation
6
33%
33%
0%
33%
33%
78
Appendix 2: Summary of Survey Results
Mobility Business Emphasis Area
Data Type
Accessible
Accurate
Complete
Credible
Timely
# of Responses
Hydraulics Infrastructure
2.50
2.73
2.36
2.73
2.50
11
Hydraulics Operation
2.63
2.75
2.63
2.75
2.43
8
Roadway Intersection
2.38
2.67
2.47
2.73
2.50
15
Economic
2.38
2.56
2.38
2.60
2.17
15
Rail Operation
2.56
2.78
2.78
2.89
2.71
9
Demographic
2.56
2.82
2.41
2.76
2.29
17
Signals and Lighting Infrastructure
2.62
2.67
2.42
2.64
2.50
12
Other Road Infrastructure Operation 2.60
2.80
2.70
2.80
2.67
10
Financial
2.37
2.74
2.37
2.63
2.24
19
Facilities Infrastructure
2.43
2.43
2.14
2.43
2.29
7
Aeronautics Infrastructure
2.80
3.00
3.00
2.80
2.50
5
Roadway Centerline
2.53
2.89
2.61
2.94
2.50
18
Surveying/Mapping
2.89
3.00
2.53
2.94
2.64
17
Transit Infrastructure
2.65
2.88
2.59
2.81
2.50
16
Traffic
2.96
2.84
2.64
2.84
2.95
24
Rail Infrastructure
2.78
2.89
2.67
3.00
2.75
9
Crash
2.70
2.74
2.48
2.87
2.29
33
Fleet Operation
2.88
3.00
3.00
3.00
3.00
8
Signs Infrastructure
2.64
2.73
2.55
2.80
2.70
11
Planned Work
2.71
2.70
2.44
2.65
2.55
26
Fleet Condition
2.78
2.78
2.89
2.89
2.88
9
Other Road Infrastructure Condition
2.53
2.59
2.47
2.59
2.57
16
Signs Operation
2.40
2.80
2.20
2.80
2.60
5
Transit Operation
2.88
2.88
2.75
2.88
2.57
8
Environmental
2.56
2.93
2.60
2.87
2.58
15
Human Resources
2.79
3.00
2.85
2.77
2.62
13
Roadway Maintenance
N/A
N/A
N/A
N/A
N/A
N/A
Signals and Lighting Operation
2.80
2.60
2.60
2.80
2.80
5
Bridge Operation
3.00
3.00
2.67
3.00
2.67
3
Pavement Condition
3.05
3.00
3.00
2.95
3.15
17
Weather
2.75
2.63
2.63
2.75
2.86
8
Construction Plans
2.81
2.96
2.68
2.88
2.73
25
Bridge Infrastructure
3.06
2.93
3.07
3.07
2.92
15
Aeronautics Operation
2.50
2.50
2.50
2.50
2.50
2
Facilities Operation
2.67
2.67
2.33
2.67
2.67
3
The Minnesota Department of Transportation
79
Safety Business Emphasis Area Summary
Data Type
Essential
Fully
Partially
Does Not
NA/ Don't Know
Total - Not Fully
Economic
14
29%
71%
0%
0%
71%
Hydraulics Infrastructure
33
21%
70%
0%
9%
70%
Demographic
18
33%
67%
0%
0%
67%
Human Resources
31
35%
55%
6%
3%
61%
Hydraulics Operation
25
32%
60%
0%
8%
60%
Financial
44
36%
57%
2%
5%
59%
Facilities Infrastructure
18
41%
53%
6%
0%
59%
Crash
39
44%
46%
10%
0%
56%
Signs Operation
25
44%
52%
4%
0%
56%
Fleet Condition
29
45%
55%
0%
0%
55%
Traffic
51
43%
53%
2%
2%
55%
Rail Infrastructure
11
36%
55%
0%
9%
55%
Facilities Operation
13
46%
46%
8%
0%
54%
Fleet Operation
26
46%
54%
0%
0%
54%
Environmental
34
41%
50%
3%
6%
53%
Other Road Infrastructure Condition
35
49%
49%
3%
0%
51%
Roadway Intersection
39
44%
44%
8%
5%
51%
Signals and Lighting Infrastructure
24
50%
50%
0%
0%
50%
Other Road Infrastructure Operation 30
43%
50%
0%
7%
50%
Signs Infrastructure
27
52%
44%
4%
0%
48%
Planned Work
52
42%
46%
2%
10%
48%
Signals and Lighting Operation
21
52%
48%
0%
0%
48%
Transit Operation
13
46%
38%
8%
8%
46%
Weather
31
55%
35%
10%
0%
45%
Aeronautics Infrastructure
7
57%
43%
0%
0%
43%
Rail Operation
7
43%
43%
0%
14%
43%
Roadway Centerline
49
55%
37%
4%
4%
41%
Transit Infrastructure
15
53%
33%
7%
7%
40%
Bridge Operation
18
56%
39%
0%
6%
39%
Roadway Maintenance
34
62%
32%
6%
0%
38%
Construction Plans
52
62%
37%
0%
2%
37%
Surveying/Mapping
38
63%
32%
3%
3%
34%
Pavement Condition
43
70%
28%
2%
0%
30%
Bridge Infrastructure
38
76%
24%
0%
0%
24%
Aeronautics Operation
5
80%
20%
0%
0%
20%
80
Appendix 2: Summary of Survey Results
Safety Business Emphasis Area Summary
Data Type
Accessible
Accurate
Complete
Credible
Timely
# of Responses
Economic
2.36
2.73
2.36
2.60
2.13
10
Hydraulics Infrastructure
2.81
2.60
2.38
2.63
2.65
24
Demographic
2.60
3.00
2.57
2.93
2.25
14
Human Resources
2.76
2.84
2.79
2.80
2.70
24
Hydraulics Operation
2.84
2.58
2.47
2.79
2.63
18
Financial
2.55
2.73
2.52
2.63
2.43
32
Facilities Infrastructure
2.50
2.58
2.42
2.82
2.67
11
Crash
2.58
2.61
2.43
2.67
2.41
34
Signs Operation
2.61
2.72
2.50
2.83
2.67
17
Fleet Condition
2.87
2.87
2.86
2.82
3.00
21
Traffic
3.00
2.82
2.68
2.91
2.89
42
Rail Infrastructure
2.80
2.80
2.40
2.80
2.60
5
Facilities Operation
2.60
2.89
2.78
3.00
3.00
9
Fleet Operation
3.00
2.95
2.95
3.05
3.07
19
Environmental
2.68
3.00
2.75
2.95
2.78
20
Other Road Infrastructure Condition
2.73
2.77
2.64
2.76
2.76
25
Roadway Intersection
2.61
2.77
2.70
2.83
2.72
29
Signals and Lighting Infrastructure
2.65
2.79
2.74
2.83
2.67
18
Other Road Infrastructure Operation 2.68
2.86
2.73
2.82
2.67
21
Signs Infrastructure
2.63
2.71
2.58
2.91
2.65
24
Planned Work
2.83
2.68
2.59
2.76
2.76
33
Signals and Lighting Operation
2.69
2.77
2.85
2.85
2.80
12
Transit Operation
2.60
2.60
2.40
2.60
2.40
5
Weather
3.00
2.52
2.72
2.64
2.83
25
Aeronautics Infrastructure
3.20
3.00
3.00
3.00
3.00
5
Rail Operation
2.60
2.80
2.80
2.80
2.75
5
Roadway Centerline
2.76
2.92
2.75
2.91
2.73
35
Transit Infrastructure
2.50
2.79
2.57
2.69
2.45
13
Bridge Operation
2.92
3.00
2.92
3.08
2.70
12
Roadway Maintenance
N/A
N/A
N/A
N/A
N/A
N/A
Construction Plans
2.96
2.98
2.83
3.00
2.84
46
Surveying/Mapping
2.73
3.13
2.79
3.08
2.81
24
Pavement Condition
3.10
2.92
2.90
3.00
3.00
38
Bridge Infrastructure
3.03
3.03
3.13
3.17
2.84
30
Aeronautics Operation
3.40
3.20
3.00
3.20
3.00
5
The Minnesota Department of Transportation
81
82
Appendix 2: Summary of Survey Results
Appendix 3: Mn/DOT Data
Management Principles
Mn/DOT manages data according to the principles identified in the Minnesota
Enterprise Technical Architecture, Revision 2.02 – 08 Sept. 2006. The Mn/DOT
Data Management Principles have been contextualized to meet the specific
needs of Mn/DOT and the department’s data custodians, stewards and users.
1. Data shall be managed as a state asset
2. Data quality fits its purpose
3. Data is accessible and shared as permitted
4. Data includes standard metadata
5. Data definitions are consistently used
6. Data management is everyone’s responsibility
7. Data shall not be duplicated
1. Data Shall Be Managed as a State Asset
Data is a valuable state resource; it has real, measureable value. The primary
purpose of data is to aid decision-making.
Rationale:

Accurate, timely data is critical to the decision-making process

Data is the foundation of decision making; therefore, we must carefully
manage data to ensure that we know what we’ve got, where it is, can rely
on its accuracy, and can obtain it when and where we need it

Facilitate department-wide or multi-jurisdictional solutions
Implications:

All Mn/DOT offices and districts must understand the relationships
between the value of data, sharing data, and accessibility to data

Employees whose positions include responsibilities for maintenance of
data in any format, must have these responsibilities clearly stated in their
job descriptions and identified as a measure in their performance review
processes

Employees with any kind of data responsibility must have the authority
and means to manage the data for which they are accountable. These
employees will be data stewards and their roles and responsibilities need
to be defined
The Minnesota Department of Transportation
83

The Business Information Council or its designated subgroup must
develop methods to prevent and correct errors in data and information
and to improve those processes that produce flawed data or information.
Data quality needs to be measured and steps taken to improve data
quality, probably resulting in policy and procedures will have to be
established

BIC or its successor should create a periodic forum, with comprehensive
representation department-wide, to decide on process changes
suggested by Data Stewards
Further work is needed to develop a framework for assessing the value and
benefit of data programs to promote efficiencies and expand utility to meet
multiple business needs.
2. Data quality fits its purpose
Data quality is acceptable and meets the business need for which it is intended.
To be fit for its purpose, data must be of sufficient accuracy and integrity
proportional to its use and cost of collection and maintenance.
Rationale:

Data is used in all areas of decision making; maintenance operations,
construction, design and administration in order for Mn/DOT to deliver its
products and services. Data is increasingly being used throughout the
organization and externally by stakeholders and customers beyond the
original purpose. Expanded use reinforces the need to ensure that the
quality of data held and managed is sufficient to meet diverse needs.

Agency data decisions should be supported by business needs, and data
categorized as agency data should be well documented, managed, and
maintained to an appropriate data quality to meet the intended business
purpose. Data which is not agency data, if held, should meet a standard
to ensure its possible use beyond the specific purpose for which it was
generated, and it is managed for integrity; otherwise, it is information and
not data and should not be shared beyond its original purpose. Data
which is not agency data, if held, would at the expense of the generating
office.
Implications:
84

A process to categorize data as agency data, other data, and information
would need to be developed. The implications of each category would
carry a responsibility for support according to a data management/data
steward policy.

The BIC or other designated governance board would be established to
evaluate data management policy, data under management, and the
costs of managing data in the agency on an annual basis. Data
Appendix 3: Mn/DOT Data Management Principles
management policy would include data documentation (metadata
requirements), data collection and manipulation processes, editing and
validation rules, historical and retention records requirements, and data
scrubbing/disposal rules.

Funding for agency level data would have to be developed as an agency
priority, funding for other data would have to be a priority for the
generating office to support in accordance with the data management
policy and practice.
3. Data is accessible and shared as permitted
Data as a valuable resource must be accessible and shared to achieve its
primary purpose as an aid in decision-making. Data accessibility and sharing
must be open to internal users in the performance of their duties and across
department functions and offices/districts. External users, partners, and
stakeholders must have access to data in accordance to applicable laws and
regulations, but beyond that as a support to decision-making processes in
product and service delivery. Mn/DOT should be seen as a trusted source of
information and data.
Rationale:





Data is accessible and restricted as permitted by law
Data is shared to the extent permitted by law
Timely access to accurate data is essential to improving the quality and
efficiency of department decision making. It is less costly to maintain
timely, accurate data in a single source and share it, than it is to maintain
duplicative data sources in multiple applications
Shared data will result in improved decisions since Mn/DOT will rely on
fewer sources of more accurate, consistent, and timely managed data for
our decision-making
For the greater good of our mission and vision, external users, partners,
and stakeholders must have access to accurate, timely data, and
Mn/DOT needs to be a trusted source of information. This transparency
and trust will build support externally for enhanced and efficient delivery of
our products and services
Implications:

There is an education task that suggests that internal users will need to
be trained in data management practice and that they will need to be
aware of what constitutes data for agency and local purposes;
furthermore, they will need to know what is accessible, where to access it,
and how to share it

To enable data sharing Mn/DOT must develop and abide by a common
set of policies, procedures, and standards governing data management
and access
The Minnesota Department of Transportation
85

Mn/DOT will need to develop standard data models, data elements, and
other metadata that defines a shared environment and develop a
repository system for storing, and managing metadata to make it
accessible

The agency is responsible for following the federal and state laws that
apply to the data they maintain and for designing information systems
accordingly

The provision of rightful access to data balanced with the protection of
data from unauthorized access must be conscientiously and continually
evaluated and applied

The electronic storage of data must incorporate a tracking method of data
classification and considerations that are known for any particular data
element, record or dataset

The process for releasing data must include steps that check against the
most current data classifications and considerations and resolve
conflicting mandates

The way information is accessed and displayed must be sufficiently
adaptable to meet a wide range of department users and their
corresponding methods or needs of access

Access to data does not constitute understanding of the data. Caution
should be taken by the Agency to ensure misinterpretation of information
is minimized for internal and external users

Data sharing will require significant culture change

The principles of data sharing will continually conflict with the principle of
data security. Under no circumstances will data sharing principle cause
confidential or private data to be compromised
4. Data includes standard metadata
Common deployment of data documentation schemes promotes data reusability,
reliability, and the possibility of sharing across the department.
Rationale:

Metadata facilitates a number of activities including data location,
retrieval, evaluation, management, use and disposition

Metadata allows data element definitions of like metadata to be shared
and help build common metadata models

Metadata allows data to be used consistently across applications
Implications:

86
Standardized procedures must be used to thoroughly document
information resources
Appendix 3: Mn/DOT Data Management Principles

Information systems should be designed the standardized metadata
scheme must be reviewed to ensure consistency

Where appropriate, employ and publish controlled vocabulary from
thesauri, standards or other controlled lists for populating specific
metadata elements
5. Data definitions are consistently used
Sharing data is best accomplished when the data is uniquely and accurately
identified. Data meaning and clarity are enforced through data element definitions
that consist of a written description of what the element is and how it is used, its
domain values, and its physical format. Data element names are structured with
consistent format and content.
Rationale:

Accurate identification ensures that data can be defined in one place,
then shared with or transmitted to another place without losing its
meaning or clarity.

Data definitions allow for maximizing the value of data resources, sharing
data with others, and meeting customer data needs.

Properly created data definitions help manage data resources by ensuring
integrity, providing clarity of meaning, and making data accessible to
those who need it through precise identification of the required data.

A good data element definition strategy with proper discipline and
management helps with data consolidations by providing a common point
of continuity. Good data names also help reduce data costs and improve
the quality of data.
Implications:

Policies, standards, and methods for data administration should be
developed at a department level.

A mechanism should be established for deciding how communities of
interest will agree on standard data definitions within their purview.

Standard definitions should be developed for qualifying department-wide
data.
6. Data management is everyone’s responsibility
All of Mn/DOT is responsible for managing data whether as an owner, steward, or
user in accordance with the department’s vision and mission for data, Mn/DOT’s
Data Management Principles, and appropriate data policies and procedures.
The Minnesota Department of Transportation
87
Rationale:

The business and technical sides of the department must come together
to manage the data from a holistic perspective.

Within the organization, agreement between what is data and what is not
must be completed. Every stakeholder will need to come together to
support developing and sustaining the information environment needs of
the agency.
Implications:

Every staff member who interacts with data must do so according to the
data vision, mission, principles, and policies.

The department should commit resources to managing data from all
offices and districts.

Achieving maximum department-wide benefit will require changes in the
way that Mn/DOT plans and manages information. Technology alone will
not bring about this change.

Some offices/districts may have to concede their own preferences for the
greater benefit of the entire department.

As needs arise, priorities must be adjusted. Through the BIC, or an
equivalent group, a comprehensive department-wide forum with broad
representation should make these decisions.
7. Data shall not be duplicated
Development of information services such as business applications, or data
warehouses available across the department is preferred over the development
of information silos which only provide data to a particular office or district.
Rationale:

Duplicative capability is expensive and propagates conflicting data.

Mn/DOT adopted a gated process for application development to control
duplication and invest in priority application development on an
organizational basis that same thinking needs to be applied to data.

Mn/DOT is data rich, but suffers quality and integrity issues from multiple
sources of conflicting data.
Implications:

88
Categorizing data as agency data will help focus resources on
consistently high quality data that is shared and accessed by multiple
agency resources. Categorizing data as other data will allow
development, sharing, and accessing data which has a narrower focus
than the agency, but still must meet a standard. Flexibility is needed for
local applications, but this is not data that would be shared or accessible
Appendix 3: Mn/DOT Data Management Principles
beyond a specific local purpose. Policy and procedures should ensure
that this is not duplicative of higher level data.

A gated process of data management and should be considered of
comparable effort to application development. Data developed at any
level will cost resources and commitment of these resources should be
weighed against the benefit of collecting that data.

Design of business services capabilities to replace/integrate silo
applications will be driven by business processes they are designed to
support.
The Minnesota Department of Transportation
89
90
Appendix 3: Mn/DOT Data Management Principles
Appendix 4: Metadata Element Standards
The Data Governance Work Team established the standard for metadata elements
which was approved by the Business Information Council in November 2009. Each
element is listed below, followed with a definition written for Mn/DOT. The mandatory
elements and definitions are based on the Dublin Core Metadata Element Set and the
Minnesota Recordkeeping Metadata Standard.
The elements should be applied at the table level, at a minimum. Ideally, they should be
applied at the column level based on the customer or business need.
Table 1: Metadata Element Standards
Element
Definition
Table Level
Column Level
Title
The name given to the entity.
X
X
Point of Contact
The organizational unit that can be
contacted with questions regarding the
entity or accessing the entity.
X
Subject
The subject or topic of the entity which is
selected from a standard subject list.
X
Description
A written account of the content or
purpose of the entity. Accuracy or quality
descriptions may also be included.
X
Update
Frequency
A description of how often the record is
update or refreshed.
X
Date Updated
The point or period of time which the
entity was updated.
X
Format
The file format or physical form of the
entity.
Source
The primary source of record from which
the described resource originated.
X
Lineage
The history of the entity; how it was
created and revised.
X
Dependencies
Other entities, systems, and tables that
are dependent on the entity.
X
The Minnesota Department of Transportation
X
X
91
92
Appendix 4: Metadata Elements Standards
Appendix 5: Data Governance Role
Responsibilities
Data Governance Board
Responsibilities
The following responsibilities for the Data Governance Board were defined by the
Data Governance Work Team and reviewed by the Business Information Council.
Since that time additional responsibilities and clarifications have been made.

Review and approve data policies, standards and procedures across the
department

Ensure that data governance strategies and processes support the
department’s mission and objectives

Direct the development of data standards across the department

Provide mechanisms for coordination, communications, information
sharing, prioritization, and conflict resolution within the department and
across projects

Provide a method to ensure accountability for the successful
implementation of all governance efforts, whether at the department level,
business units or projects

Help define the business case for data management projects and
oversees project status and progress

Coordinate efforts with the project management function in the Office of
Information & Technology Services (OI&TS) so projects can be included
in the overall IT project portfolio

Assist in establishing stewardship organizations by developing a method
to appoint stewards

Plan and sponsor data management projects

Develop a work plan to clarify and implement the responsibilities
Data Stewardship Steering Committee
Responsibilities
The following responsibilities will ensure support and oversight of various data
initiatives. The Data Governance Board may delegate additional responsibilities
to Data Stewardship Steering Committees depending on the nature of the team
and as data governance matures at Mn/DOT.
The Minnesota Department of Transportation
93

Provide business expertise regarding data and represent all data
stewards

Review and approve changes to data definitions and use

Review and approve logical data models

Ensure application data requirements are met

Review data quality analysis and audits
Assign the following roles or collaborate with other data stewards to fulfill the
following responsibilities:

Business Process Analyst - Responsible for understanding and optimizing
business processes

Collaborator - Engage in data sharing agreements across functions

Subject Matter Expert (SME) – Significant experience or knowledge of a
given function

Knowledge Workers – Consumer of the data and information to do his/her
job
Data Stewards
Responsibilities
94

Collaborate with and engage a variety of data stakeholders and
customers in decisions relating to data sets

Propose, draft, review, and refine business names, definitions, and other
data model specifications for assigned data

Ensure the validity and relevance of assigned data

Define and maintain data quality requirements and business rules for
assigned data

Maintain assigned data definitions and use

Identify and help resolve data issues

Assist in data quality analysis and improvement

Provide input to data policies, standards and procedures
Appendix 5: Data Governance Role Responsibilities
Data Management Coordinator
Responsibilities
The Data Management Coordinator coordinates data governance and
stewardship activities for the organization and the Data Governance Board. In
addition to these responsibilities, the Data Management Coordinator will:

Support the activities and decision-making processes of the Data
Governance Board and data stewards

Participates on and provides staff support to all Data Steward Steering
Committees

Help executives identify and appoint data stewards

Schedule and plan meetings of the Data Governance Board and data
stewardship steering committees

Manage and coordinate resolution of data issues

Assist in definition and framing of data issues and solution alternatives

Assist in definition of data management policies and standards

Assist in understanding business information needs

Act as a liaison between the business and IT needs relating to data

Provides expertise in data governance best practices
The Minnesota Department of Transportation
95
96
Appendix 5: Data Governance Role Responsibilities
Appendix 6: Complete List of Data Management
Roles
The table on the following pages is a summary of the recommended data management
roles to be implemented or formalized in the Department. The current estimates are
accumulative totals of staff performing roles with consideration for the gap analysis.
The Minnesota Department of Transportation
97
Table 2: Data Management Roles
Role
Responsibilities
Data Governance Board Chair
Fulfills the responsibilities of business data stewardship at a strategic level.
Data Governance Board Member
Serve on the board by representing dept.-wide data interests.
Data Stewardship Steering Committee Support the board by drafting policies, standards or working on specific initiatives.
Member
Data Coordinator
Coordinate activities of data stewards and support actions of the Data Governance Board.
Data Steward
Represent and be accountable for assigned data set(s) and insure the quality and adherence
to data principles.
Data Management Coordinator
Coordinate data governance and data stewardship activities, oversee data management
projects, and lead data management professionals.
Business Process Analyst
Understand and optimize business processes relating to data.
Collaborator
Engage in data sharing agreements across functions.
Subject matter Expert (SME)
Share experience or knowledge of a given business function relating to data.
Knowledge Worker
Uses data and information to complete work assignments.
Data Architect
Data architecture and data integration.
Data Integration Architect
Designs technology to integrate and improve the quality of the department’s data assets.
Data Integration Specialist
Implements systems to integrate (replicate, extract, transform, load) data assets.
Database Administrator
Designs, implements and supports structured data assets.
Data Model Administrator
Performs data model version control and change control.
Data Analyst / Data Modeler
Captures and models data requirements, data definitions, business rules, data quality
requirements, and logical and physical data models.
Data Quality Analyst
Determines the fitness of data for use.
Metadata Specialist
Integrates, controls, and delivers metadata including administration of metadata repositories.
Analytics / Report Developer
Creates reporting and analytical application solutions
Data Warehouse Architect
Data warehouses, data marts, and associated data integration processes
Business Intelligence Analyst/
Administrator
Supports effective use of business intelligence data by business professionals
98
Appendix 6: Complete List of Data Management Roles
Role
Recommendations
Current staffing
levels (FTE est.)
Gap
Data Governance Board Chair
One residing in a District/Office
0
Needs to be assigned
Data Governance Board
Member
Seven distributed between divisions
and Finance
0
Needs to be assigned
Data Stewardship Steering
Committee Member
TBD based on Data Governance
Board needs
0
Assigned based o n board needs
Data Coordinator
TBD based on data domains
identified by board
0 (formally)
Need to be formally assigned to data
domains
Data Steward
TBD based on data sets identified
by board
0 (formally)
Need to be formally assigned to data sets
Data Management Coordinator One centralized in Dept.
0
Needs to be assigned
Business Process Analyst
TBD based on need
0 (formally)
Identified by data coordinators/ stewards to
aid in data quality/ decisions
Collaborator
TBD based on need
0 (formally)
Identified by data coordinators/ stewards to
aid in data quality/ decisions
Subject matter Expert (SME)
TBD based on need of data
stewards
0 (formally)
Identified by data coordinators/ stewards to
aid in data quality/ decisions
Knowledge Worker
NA
>4000
NA
Data Architect
One IT role centralized in Dept.
1 central IT
position
Adequate staffing levels
Data Integration Architect
One IT role centralized in Dept.
0
Needs to be filled
Data Integration Specialist
Multiple based on workload
strategically distributed in the Dept.
.5 distributed
1.5 centralized Adequate staffing, filled
on a project by project basis
Database Administrator
Multiple based on workload
strategically distributed in the Dept.
1.5 distributed
4.25 centralized
Adequate staffing levels
Data Model Administrator
One IT role centralized in Dept.
0
Needs are not being met
Data Analyst / Data Modeler
Multiple based on workload
strategically distributed in the Dept.
3 distributed
5.75 centralized
Adequate staffing levels
Data Quality Analyst
Multiple based on workload
strategically distributed in the Dept.
As needed
distributed
4.5 centralized
Be more proactive in IT, Review consultant
requirements, and all data stewards should
ensure data quality responsibilities
Metadata Specialist
One lead specialist per project, #
based on workload
2.25 centralized
Under staffed centrally and contracted
projects
Analytics / Report Developer
Multiple based on workload
strategically distributed in the Dept.
2 distributed
4 centralized
Current levels are adequate, although
needs change as auditing increases and
tools like BI become available.
Data Warehouse Architect
One IT role centralized in Dept.
1 centralized
Current levels are adequate
Business Intelligence Analyst/
Administrator
The Minnesota Department of Transportation
99