data business plan recommendations

Data Business PlanMinnesota 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 Executive Summary8 Data Business Plan recommendations10 Conclusion

13 Chapter 1: Introduction13 Background13 Data challenges and opportunities in Mn/DOT15 Why develop a business information plan?16 Business information planning in Minnesota16 Vision16 Mission

19 Chapter 2: Assessing the current state of data at Mn/DOT19 Background19 Process23 Infrastructure preservation findings and recommendations25 The core principles of asset management26 Examples of Infrastructure Preservation Data Gap Needs28 Traveler safety findings and recommendations30 Examples of traveler safety data gaps and needs32 Mobility findings and recommendations 35 Additional Priority and data gaps and needs39 Concluding thoughts on data gaps and needs

41 Chapter 3: Data Governance 41 Background42 Data governance framework42 Principles44 Policies44 Standards45 Roles45 Data governance board47 Data Stewardship Steering Committee(s)48 Data stewards49 Data management coordinator51 Processes51 Integration with the division directors’ investment management process52 Department IT architecture 52 Business data catalog 53 Conclusion

55 Chapter 4: Geographic Information Systems introduction55 Background


55 GIS industry directions and trends57 A tool in the toolbox57 Identify core geographic information system spatial data needs58 Provide strategic direction for GIS to address business needs for

geospatial data 60 Strengthen GIS business support61 Align data governance and GIS63 Vision63 Goals63 Objectives66 Strategic planning for GIS67 Conclusion

69 Chapter 5: Conclusion

71 Appendix 1: BIC-GIS Members71 BIC-GIS Work Team:71 GIS Strategic Plan Revision Participants: 72 Mn/DOT Business Information Council

75 Appendix 2: Summary of Survey Results76 Preservation Business Emphasis Area78 Mobility Business Emphasis Area80 Safety Business Emphasis Area

71 Appendix 3: Mn/DOT Data Management Principles

75 Appendix 4: Metadata Element Standards

65 Appendix 5: Data Governance Role Responsibilities65 Data Governance Board65 Data Stewardship Steering Committee66 Data Stewards66 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.


VisionAll Mn/DOT business decisions will are supported by reliable data

MissionProvide reliable, timely data and information that is easily accessed, shared for analysis and integrated into Mn/DOT’s decision-making process

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:

Three separate tracts were implemented to accomplish data business planning activities.

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 Needs1. Develop an asset management framework for Mn/DOT (pg. 24)

8 Executive Summary

1. Data will be managed as state assets2. Data quality will fit its purpose3. Data will be accessible and shared as permitted4. Data will include standard metadata5. Data definitions will be consistently used6. Data management is everybody’s responsibility7. Data shall not be duplicated8. Data Business Planning Tracks

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

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 Governance1. 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)


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)

ConclusionMn/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.


Chapter 1: Introduction

BackgroundTransportation 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/DOTEffective 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

12 Chapter 1: Introduction

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


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.

Business Information Planning in MinnesotaIn 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.


VisionAll Mn/DOT business decisions will are supported by reliable data

MissionProvide reliable, timely data and information that is easily accessed, shared for analysis and integrated into Mn/DOT’s decision-making process

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.


Chapter 2: Assessing the current state of data at Mn/DOT

BackgroundAssessing 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

ProcessThe 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:

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 17

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

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 usersIn 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 groupsFollowing the survey, individual traveler safety, preservation and mobility focus groups were created to discuss survey findings and results.

18 The Minnesota Department of Transportation

Figure 2.1: Data Business Plan framework for accessing the current state of data at Mn/DOT


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 improvementIn 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, 2012In 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


those recommendations and strategies that were identified as high priorities for the first data business planning effort.

Infrastructure preservation findings and recommendationsInfrastructure 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


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 long-term 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


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.


The core principles of asset management Policy-driven — Resource allocation decisions are based on a well-

defined 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.

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 high-priority 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:

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


→ 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 three-year 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


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 recommendationsTraveler 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:

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


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


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.


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


Mobility findings and recommendationsMn/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


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 non-reoccurring 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.


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


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 NeedsThe 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


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


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


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


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 needsThis 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.


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.


Chapter 3: Data Governance

BackgroundEveryone 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 hierarchy2

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

More department-wide spatial data tools

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 39

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 frameworkAccording 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.

Principles

3 DAMA Data Management Book of Knowledge. page 18.

4 DAMA Data Management Book of Knowledge. page 37.


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

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.

PoliciesPolicies 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.


StandardsSimilar 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.

RolesMn/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.


Data governance boardThe 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.

MembersThe 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.

ChairThe 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


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.


Figure 3.4: Relationship between data level

Data StewardsData 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

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 CoordinatorThe 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.


Figure 3.5: Relationship between data roles

Figure 3.6: Mn/DOT example of Data Coordinator and Data Steward

(Illustrative use only)


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.

ProcessesSeveral 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 processWhile 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.


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.

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.


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

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 multi-step 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.

ConclusionImplementing 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 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.

BackgroundMn/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 trendsGIS 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.

52 Chapter 4: Geographic Information Systems Introduction

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


becoming more accepted for obtaining information, the public’s skill level has increased.

A tool in the toolboxMn/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 needsMn/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


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. Where is aging infrastructure failing to meet targets?2. Where are wetlands being removed and where are they being replaced?3. What are regional demographics by area?4. Where is congestion occurring? What are alternative routes?5. 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


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 decision-making 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:


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 supportThere 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.


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 GISGeographic 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 assetData 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.


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 purposeTo 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.


Figure 4.1: Vision, goals, objectives and strategies

VisionEnhance the business decision-making process through the availability of a high quality Geographic Information System.

Goals1. GovernanceEstablish and promote GIS standards and best practices within the department

2. GuidanceImprove the GIS knowledge base within the department

3. SustainabilityDeploy resources to enable efficient GIS integration and growth

4. Data Services and SupportDeploy 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

Educate all levels of users on current and potential use of GIS

Provide GIS training to varied audiences to increase the skill level of all levels of GIS users

Establish processes to review and support development of business processes to enable integration and efficiency

Develop an ongoing GIS support system to enable efficient use of department-wide GIS resources

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

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


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.


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 usedSharing 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.


Strategic planning for GISMn/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 technologyFigure 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.


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.

ConclusionThis 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


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.


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.

66 Chapter 5: Conclusion

5. Business intelligence recommendations highlight the value of department-wide 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.


Appendix 1: BIC-GIS Members

BIC-GIS Work Team: GIS Strategic Plan Revision Participants:

Elizabeth BenjaminLee Berget, ChairLisa BinghamPeter BuchenGlen EllisGary FriedBrian GageJoella GivensCory JohnsonRocky HaiderKathy HofstedtRick KostohryzMatt KoukolJonette KreideweisMike LeegardSusan LodahlErnest LloydThomas MartinRobert MillerRick MoreyTim Quinn, ChairMike ReynoldsDan RossMary SafgrenMike SchadeggTim SpencerAndy Trcka (Staff)Susan Walto (Staff)Paul WeinbergerSusan Zarling

Steering Team:Lee BergetTim QuinnJonette KreideweisDan RossKathy HofstedSusan Walto (staff)Andy Trcka (staff)

Edit Team:Matt KoukolSusan WaltoAndy TrckaBrian GagePaul WeinbergerPeter Morey

Goal 1 (Governance):Thomas MartinErnest LloydSusan WaltoRick MoreyPeter DahlbergRyan WilsonCharlie McCarty

Goal 2 (Guidance)Joella GivensGlen EllisSue ZarlingJesse PearsonAndy Trcka Lisa Bingham

Goal 3 (Sustainability)Peter MoreyDan RossRocky HaiderBrian GageGary FriedLiesa Miller

Goal 4 (Data Service & Support)Mary SafgrenPaul WeinbergerJoella GivensMatt KoukolMike ReynoldsAdam Julson

68 Appendix 1: BIC–GIS Members

Mn/DOT Business Information CouncilCouncil 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

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

70 Appendix 1: BIC–GIS Members

Appendix 2: Summary of Survey Results

Response KeyEssential = # 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.

72 Appendix 2: Summary of Survey Results

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%


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


Mobility Business Emphasis Area





Economic 18 28% 67% 6% 0% 72%

Rail Operation 10 10% 60% 10% 20% 70%

Demographic 20 30% 65% 5% 0% 70%



Financial 25 36% 64% 0% 0% 64%



Roadway Centerline 22 41% 59% 0% 0% 59%



Traffic 29 34% 59% 0% 7% 59%


Crash 24 42% 50% 8% 0% 58%

Fleet Operation 9 44% 56% 0% 0% 56%


Planned Work 33 33% 52% 0% 15% 52%

Fleet Condition 10 50% 50% 0% 0% 50%


Signs Operation 6 50% 50% 0% 0% 50%


Environmental 23 48% 48% 0% 4% 48%

Human Resources 17 53% 47% 0% 0% 47%



Bridge Operation 5 60% 40% 0% 0% 40%

Pavement Condition 20 60% 35% 5% 0% 40%

Weather 10 60% 20% 20% 0% 40%


Bridge Infrastructure 18 56% 39% 0% 6% 39%




Mobility Business Emphasis Area





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



Financial 2.37 2.74 2.37 2.63 2.24 19



Roadway Centerline 2.53 2.89 2.61 2.94 2.50 18



Traffic 2.96 2.84 2.64 2.84 2.95 24


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


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


Signs Operation 2.40 2.80 2.20 2.80 2.60 5


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



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


Bridge Infrastructure 3.06 2.93 3.07 3.07 2.92 15




Safety Business Emphasis Area Summary


Economic 14 29% 71% 0% 0% 71%


Demographic 18 33% 67% 0% 0% 67%

Human Resources 31 35% 55% 6% 3% 61%


Financial 44 36% 57% 2% 5% 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%



Fleet Operation 26 46% 54% 0% 0% 54%

Environmental 34 41% 50% 3% 6% 53%






Planned Work 52 42% 46% 2% 10% 48%



Weather 31 55% 35% 10% 0% 45%


Rail Operation 7 43% 43% 0% 14% 43%

Roadway Centerline 49 55% 37% 4% 4% 41%


Bridge Operation 18 56% 39% 0% 6% 39%




Pavement Condition 43 70% 28% 2% 0% 30%

Bridge Infrastructure 38 76% 24% 0% 0% 24%



Safety Business Emphasis Area Summary


Economic 2.36 2.73 2.36 2.60 2.13 10


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


Financial 2.55 2.73 2.52 2.63 2.43 32


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



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






Planned Work 2.83 2.68 2.59 2.76 2.76 33



Weather 3.00 2.52 2.72 2.64 2.83 25


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


Bridge Operation 2.92 3.00 2.92 3.08 2.70 12




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



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 AssetData 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 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 purposeData 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: 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


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 permittedData 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


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 metadataCommon 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: Standardized procedures must be used to thoroughly document

information resources


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 usedSharing 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 responsibilityAll 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.


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 duplicatedDevelopment 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: 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


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.


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 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.

X

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


88 Appendix 4: Metadata Elements Standards

Appendix 5: Data Governance Role Responsibilities

Data Governance BoardResponsibilitiesThe 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 CommitteeResponsibilitiesThe 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.


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 StewardsResponsibilities

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

90 Appendix 5: Data Governance Role Responsibilities

Data Management CoordinatorResponsibilitiesThe 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


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.


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 Member

Support the board by drafting policies, standards or working on specific initiatives.

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


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


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 distributed5.75 centralized


Data Quality Analyst Multiple based on workload strategically distributed in the Dept.

As needed distributed4.5 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 distributed4 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


data business plan recommendations

Documents