U.S. Department of Transportation Roadway Transportation Data Business Plan (Phase 3): Data Business Plan Development for State and Local Departments of Transportation

Chapter 2. Data Business Plan Development

This section provides assistance for State and local Departments of Transportation (DOTs) to develop a data business plan (DBP) for roadway travel mobility data, including stakeholder outreach, data assessment, gap assessment, improvement plan, data governance processes and documents, and data management practices. The audience is intended to be State and/or local DOTs or Metropolitan Planning Organizations (MPO's). The term "lead agency" is used to represent the agency leading the effort to develop the DBP.

Figure 1 depicts the steps of the DBP.

Step 1. Establish Need And Objectives

A lead agency should begin by establishing the need and objectives for the DBP. This involves examining the high-level challenges and opportunities for improving mobility data in the region. For example, an agency may wish to address stakeholder needs for specific mobility data systems (e.g., data systems, data elements, data collection methods, duplicative data collection efforts, data storage environments, quality of data, data standards, data integration, data analysis, documentation, and system access), technology and tools for managing data (e.g., software, hardware, system interfaces, Information Technology (IT) compatibility, business intelligence tools, analytical tools, knowledge management, and network issues), or the management/governance of the data (e.g., business rules and processes, data management, data governance, coordination across business lines, resource availability, and training needs). Some pilot sites found it beneficial to obtain input from executive leadership regarding how the DBP fits into the larger agency goals/direction.

Lead agencies should also develop an outcome statement describing the results the DBP will achieve. Example outcome statements are below:

• Hillsborough MPO: The expected outcome of the DBP is a framework for partner agencies to share travel time and speed data for roadway users and freight within the tri-county region for planning purposes.
• Mid-America Regional Council: The expected outcome of this effort is to develop a process for developing, collecting, calculating, and reporting on performance measures to support mobility in the region.

The Maryland DOT State Highway Administration (SHA) used the DBP to develop a Framework representing the interaction, structure, and components for Maryland DOT SHA to integrate and report on mobility data. It has three components:

• Data—Description of data elements including data inventory and required improvements related to availability, timeliness, coverage, and quality.
• Architecture—A high-level description of the interaction between databases and tools to support use of the integrated mobility data.
• Governance—Components of an institutional structure describing roles and responsibilities related to ensuring all data is available.

Maryland DOT SHA also defined three tiers of data to assist with prioritizing action items in the plan. They are:

• Tier 1. Traffic volume and speed.
• Tier 2. Origin/Destination, accessibility, truck freight, work zone and signal timing.
• Tier 3. Connected and Automated Vehicle.

Step 2. Stakeholder Outreach

The next step is to identify and document the stakeholders for roadway travel mobility data. Stakeholders include any internal or external person or organization that collects, owns, maintains, uses, interfaces with, accesses, or benefits from roadway travel mobility data. These stakeholders play a vital role in identifying the business needs and uses for roadway travel mobility data from the perspective of their individual offices or agencies.

Internal stakeholders may include those involved in traffic operations, traffic safety, roadway design, pavement design, maintenance, air quality, modal, and connected vehicle capture activities. External stakeholders may include State and local transportation agencies, traffic management centers, transportation system managers, Corridor Coalitions, transit agencies, metropolitan planning organizations, researchers, freight operators, private data providers (e.g., Inrix, Nokia-Navteq-HERE, TomTom, TrafficCast, etc.), neighboring State DOTs, media providers, the traveling public, and FHWA.

A lead agency should develop a stakeholder registry and plan for engaging stakeholders throughout each step of the DBP development process. The registry should include contact information for each stakeholder, including name, agency/office name, email, and phone number. The plan should identify the stakeholders that are relevant for each step of developing the DBP, the feedback desired for that step, and engagement mechanisms (e.g., in-person meetings, surveys, focus groups, workshops, research studies, briefings, etc.).

An example of a Stakeholder Engagement Plan is shown in table 1.

Table 1. Sample stakeholder engagement plan.

Data Business Plan Development Process	Key Actions	Relevant Pilot Site Stakeholders	Stakeholder Input Needed	Outreach Mechanism
Step 1. Stakeholder Outreach	Identify stakeholders and document their input. Develop stakeholder registry and plan for engaging stakeholders.	Pilot Site Champions	Obtain input on regional stakeholders to include in the Data Business Plan development effort.	Phone interviews
Step 2. Data Assessment	Identify issues related to the collection, management, governance, or use of mobility data programs and stakeholder cooperation / coordination. Assess level of maturity within assessment areas using a Data Management Maturity Model.	Pilot Site Champions Regional Stakeholders	Obtain input on specific issues, symptoms, and root causes within each assessment area. Obtain input on maturity within each assessment areas.	Stakeholder survey Phone interviews Stakeholder workshop
Step 3. Gap Assessment	Identify gaps and overlaps that exist in program activities related to data systems, technology and tools, and data governance, culture, and collaboration.	Pilot Site Champions Regional Stakeholders	Obtain input on what mobility data is being collected within their organizations and at the regional level, how the data supports mobility planning, operations and performance measure activities, and who is responsible for managing/updating data. Obtain consensus on gaps and overlaps that exist in program activities related to data systems, technology and tools, and data governance, culture, and collaboration.	Stakeholder survey Phone interviews
Step 4. Improvement Plan	Identify improvements needed to address gaps within each assessment area. Identify desired future condition. Identify strategies/actions needed to move to next level of capability. Prioritize strategies/actions. Develop Improvement Plan. Revise the Improvement Plan as needed.	Pilot Site Champions Regional Stakeholders	Obtain input on improvements needed to address gaps. Obtain input on desired maturity level and steps needed to achieve the goals and objectives of the DBP. Obtain input on priorities and schedule for implementing strategies/actions. Assign responsibilities for planned implementation (to be formalized through a charter). Obtain updates on shifting priorities or other data management/governance initiatives.	Phone interviews
Step 5. Data Governance Processes and Documents	Develop data governance model. Determine data governance roles and responsibilities. Develop supporting documentation.	Pilot Site Champions Regional Stakeholders	Obtain consensus on the data governance model and data governance roles and responsibilities. Obtain input and consensus on supporting documentation.	Phone interviews
Step 6. Data Management Practices	Identify data management practices, standards, and policies needed to support management of mobility data.	Pilot Site Champions Regional Stakeholders	Obtain input on data management practices, standards, and policies needed in each focus area.	Phone interviews
Step 7. Develop Data Business Plan	Document the Data Business Plan.	Pilot Site Champions Regional Stakeholders	Obtain feedback on the Data Business Plan	Phone interviews Stakeholder workshop
Step 8. Implement Data Business Plan	Execute the strategies/actions contained in the Improvement Plan. Formalize roles and responsibilities to support data governance. Implement performance measures to track success. Report on implementation progress.	Pilot Site Champions Regional Stakeholders	Obtain feedback on proposed revisions of the Data Business Plan. Obtain feedback on training needs and plan effectiveness. Provide an update on plan implementation and seek strategic direction from senior management.	N/A

Agencies may choose to send a project kick-off letter to stakeholders to inform and obtain their support for the DBP effort. An example stakeholder letter is provided in appendix A. The lead agency may also choose to execute cooperative agreements with some of the neighboring stakeholders. An example Memorandum of Understanding and Data Sharing Agreement are provided in Appendices B and C, respectively. Finally, the agency may wish to designate a smaller group of stakeholders as "partners" if they have a larger stake in the process. Stakeholder outreach mechanisms could include interviews, surveys, and workshops.

Step 3. Data Assessment

The next step is to identify the data sets and business uses for mobility data they are interested in addressing with the DBP. For example, there may be particular interest in integrating speed and volume data to report on mobility performance measures. Another example could be the need to collect and integrate speed, travel time and incident data for analyzing bottlenecks or impact of operations projects on arterials. Some pilot sites found it helpful to develop a data inventory to increase their knowledge of partner agencies' current and future mobility data collection activities. The inventory included the following information: organization, mobility data collected, data source, data collection method, network type, geographic boundary, time period, real-time versus archived, and purpose.

The following tables are excerpts of data inventories from two of the pilot sites.

Table 2. Excerpt of data inventory from Hillsborough Metropolitan Planning Organization pilot.

Organization	Mobility Data Collected	Data Source	Data Collection Method	Network Type	Geographic Boundary	Time Period	Real Time versus Archived	Purpose
Tampa-Hillsborough Expressway Authority (THEA)	As a toll road, THEA primarily collects transaction data. However, they do collect some mobility data such as traffic volume counts and speeds. It is collected using microwave. They are installing Bluetooth as part of an Intelligent Transportation System project.	Obtained from another agency—Florida DOT Other—If we need travel speed, we will do traffic engineering studies.	Bluetooth (FUTURE)	Highways	Lee Roy Selmon Expressway, Meridian Avenue, and Brandon Parkway.	Samples	Real-time Archive	Operations Planning
Hillsborough County	Speed (FUTURE) Travel times (FUTURE)	Other—Google Traffic/Waze (FUTURE)	Other—Crowdsourcing (FUTURE)	Freeways (FUTURE) Highways (FUTURE) Arterials (FUTURE)	Within Hillsborough County (FUTURE)	Ongoing (FUTURE)	Real-time (FUTURE)	Operations (FUTURE)
City of Tampa	Volume Speed Travel times	Obtained from another agency—Florida DOT Other—Google Traffic/Waze Collected internally using machine counters and laser/radar devices.	GPS Bluetooth/BlueTOAD Other—Crowdsourcing Other—machine counter and laser radar devices.	Freeways Highways Arterials	Within the City of Tampa and adjacent surrounding areas.	Ongoing Samples	Real-time Archive	Operations Planning

Table 3. Excerpt of data inventory from Mid-America Regional Council (MARC) pilot.

	Organization
	City of Overland Park, KS	Kansas City Area Transportation Authority (KCATA)
Mobility Data Collected	Bicycle Volume, Vehicular Volume, Vehicular Speed	Number of transit boardings by stop, transit on-time arrival, transit ridership, transit travel time, and other data (including General Transit Feed Specification (GTFS), operational statistics, maintenance, etc.).
Data Source	All are collected internally.	All are collected internally.
Network Type	Arterials and collectors	A variety of facilities, including local, arterials, and freeways.
Geographic Boundary	Overland Park	KCATA Region
Data Collection Standards	Yes	Yes, but transit on-time arrival is not adequate, and other datasets are uncertain regarding adequacy.
Meeting Business Needs?	Yes for bicycle and vehicular volume. No for vehicular speed.	Not for on-time arrival. Undefined/ unknown for the rest.
If No, why Not	"The speed data is random (when residents complain about speeding in their neighborhood) and sometimes quite old data is used."	"On-time arrival information definition for data collection doesn't match the way public would see as on-time. Some technical issues."
Data Sharing	The volume counts are shared with MARC and the general public.	Ridership is publicly available. Other datasets are shared internally and with other organizations.
Data Sharing Obstacles		There is no good structure or interface for sharing on an ongoing basis.
Data Documentation		Bad for on-time arrival. Ok for the rest.
Data Management Structure	To manage this data, certain individuals or work groups are tasked with developing count needs and deploying equipment.	No
Collaboration	They have a quarterly meeting with the Johnson County Traffic Engineers to discuss common areas of interest	Currently working on a new regional dashboard. Collaboration with MARC and local jurisdictions, sharing data on an as-needed basis.

Next, the lead agency should conduct an assessment to identify issues related to the collection, management, governance, or use of roadway travel mobility data programs and stakeholder cooperation/coordination. The lead agency can use the following questions to help identify specific issues, symptoms, and root causes that need to be addressed in the DBP:

Data Systems:

• Are there gaps in required data elements needed to support mobility planning, operations, and performance measure activities? If so, what are they?
• Are current data collection efforts meeting business needs? If not, why not?
• Are there overlaps or redundancies occurring in current data collection or data management efforts? If so, what are they?
• Are business processes for data acquisition and updating, quality assurance, data processing, and use documented? If so, what are they?
• Is there an inventory of available roadway travel mobility data systems (in a data registry)? If so, is it adequate?
• Are data collection standards and metadata in place? If so, are they adequate?
• What are the needs for integrating roadway travel mobility data sets to support performance measurement and asset management purposes?
• Have links been created between existing data sets and connected vehicle data sets, or is there a need to do this in the future? If so, what are they? If not, should there be?
• What business needs or business decisions would be supported through data integration?
• Are data easily accessible? If not, what improvements are needed?
• Are users able to find the data they need and in the format they need it in? If not, why not?
• Are there any opportunities for sharing of data with internal/external stakeholders, thereby reducing costs associated with data collection?

Technology and Tools:

• Do users have access to the business analysis tools they need to support mobility planning, operations, and performance measure activities? If not, why not?
• Are technology/tools that support data management and analysis consistent, standardized, and updated? If not, what improvements are necessary?

Data Governance, Culture, and Collaboration:

• Are roles, responsibilities, and processes for managing/updating the data formalized and documented?
• Is there a data governance structure in place, including formally defined roles and responsibilities, communities of interest, formation of data governance council, development of data governance manual, and data catalog? If not, should there be?
• Does top management visibly support data management/governance efforts? If not, why not?
• Are adequate resources committed? If not, why not?
• Is data being promoted as a DOT-wide asset? If not, why not?
• How is the program made visible and relevant to management and DOT staff?
• Are internal/external partner agencies appropriately aligned and working together productively? If not, what changes are necessary?
• What topics do stakeholders currently collaborate on (e.g., sharing request for proposals (RFPs) for current and upcoming initiatives, procurement plans, program roadmaps, vision/objective documents, sharing of current initiatives, activities, and best practices related to specific types of mobility and connected vehicle data)?
• How does collaboration take place? Has collaboration been successful? What factors have contributed to success/failure?

The lead agency should assess their current level of maturity within each of the assessment areas above using a Data Management Maturity Model. The maturity model helps agencies assess their current capabilities with respect to data management and governance and identify next steps in achieving the goals and objectives of the DBP. There are three distinct levels of capability:

• Level 1—Initial/Under Development. Activities and relationships are largely ad hoc, informal, and champion-driven, substantially outside the mainstream of other DOT activities. Alternatively, the capability is under development, but there is limited internal accountability and uneven alignment with other DOT activities.
• Level 2—Defined/Managed. Technical and business processes are implemented and managed, partnerships are aligned, and training is taking place.
• Level 3—Optimized. Data management and governance is a full, sustainable DOT program priority, with continuous improvement, top-level management support, and formal partnerships in place.

The Maturity assessment be performed for each of the above categories. The agency can assign a level score according to current and desired conditions. The agency should also consider the timeframe and whether the desired state is constrained or unconstrained.

Figure 2 is an example of results of the maturity assessment for one of the pilots.

The pilot sites used stakeholder surveys and workshops for gathering information for the inventory and assessment. An example stakeholder survey is provided in appendix D. Appendix E contains best practices for designing and administering the survey.

Step 4. Gap Assessment

The assessment results will help the lead agency and local partners understand what roadway travel mobility data is being collected within their organizations and at the regional level, how the data supports mobility planning, operations and performance measure activities, and who is responsible for managing/updating the data. A lead agency should examine the assessment results and identify any gaps and overlaps that exist in program activities in each of the following improvement areas:

• Data Systems: Gaps related to data systems, data elements, data collection methods, duplicative data collection efforts, data storage environments, quality of data, data standards, data integration, data analysis, documentation, and system access.
• Technology and Tools: Gaps related to software, hardware, system interfaces, IT compatibility, business intelligence tools, analytical tools, knowledge management, and network issues.
• Data Governance, Culture, and Collaboration: Gaps related to business rules and processes, data management, data governance, coordination across business lines, resource availability, and training needs.

Table 4 is an example of a gap summary from one of the pilots.

Table 4. Example summary of gaps.

Dimension	Gaps
Data Systems	Gaps in travel time/speed data, turning movement counts at intersections, origin/destination data, pedestrian/bicycle activity data, and data to support calculation of return on investment.
	Need to assess how connected vehicle data could be incorporated into the Multimodal Transportation Database and used for planning purposes.
	Need improved data quality/data collection standards for travel time/speed data.
	Need to define data standards for Bluetooth/GPS probe data.
	Need to make better use of expanding data sources for performance management.
	Need to develop/formalize business processes for the following: Systematics process to gather travel time/speed data from partner agencies. Procedures for managing and analyzing mobility data. Procedures for attaching travel time data to roadway segments in the Multimodal Transportation Database. Procedures for analysis such as determining the average travel time and standard deviation during the PM peak on a typical weekday, or determining whether there is a correlation between travel time on arterials and fatality rates.
	Need method for data integration.
	Need to improve the structure of the Multimodal Transportation Database to support data integration.
	Need data sharing platform to support external partner agency access to the Multimodal Transportation Database.
	Need to address proprietary and personally identifiable information (PII) data restrictions.
	Need to address data storage issues associated with data size.
Technology and Tools	Need more robust analysis tools to handle large datasets.
	Need staff training on use of analysis tools.
	Need to address network conflations issues associated with NPMRDS/HERE data.
	Need to address network-testing issue.
Data Governance, Culture, and Collaboration	Need improved collaboration among partner agencies to increase awareness of mobility data availability.
	Need a formal governance or collaboration program.
	Need systematic process for sharing data with partner agencies.

Step 5. Improvement Strategies

Once a lead agency has identified the gaps in roadway travel mobility data programs and data management/governance practices, it should identify improvements needed to address the gaps within each area. One way to do this is to compare the current situation to a desired future condition and identify strategies needed to move to the next level of capability.

A lead agency should prioritize the strategies based on input from data system owners and/or directives from senior management. A priority for implementation may be assigned as follows:

• High—Strategies/actions that should be implemented as soon as possible as they significantly improve the assessment dimension and gaps.
• Medium—As time and investments permit, these strategies/actions should be implemented.
• Low—The benefit provided by these strategies/actions do not significantly improve the assessment dimension and gaps. These strategies/actions can be implemented as time and investments permit, but are lowest in priority.

The result of this step is a table summarizing the strategies/actions, the offices responsible for implementing each action, and an implementation schedule. In addition, a lead agency should identify opportunities for collaboration to address these issues. The lead agency should review and revise the schedule as needed to reflect any shifting priorities or other data management/governance initiatives within stakeholder offices.

Following is an excerpt from one of the pilots.

Table 5. Excerpt of improvement strategy table.

Dimension	Sub Area	Strategies	Priority
Data Systems	Data Collection/Acquisition	Incorporate traffic count data from other local agencies into the Multimodal Transportation Database. Initial efforts should focus on short-term count data from Hillsborough and Pinellas MPOs.	High
		Address gaps in travel time/speed data, turning movement counts at intersections, origin/destination data, pedestrian/bicycle activity data, and data to support calculation of return on investment.	Medium
		Address data gaps to meet requirements of the MAP-21/FAST Act Performance Management regulations.	High
		Utilize NPMRDS travel time data and combine it with regional traffic volume data.	Medium
		Archive travel time/volume data and make it available to support compliance with Performance Management regulations.	High
		Develop specifications for collecting, updating, maintaining, and archiving mobility data in the Multimodal Transportation Database and assign responsibility for these activities.	High
		Develop systematic process to gather/update travel time/speed data from partner agencies.	Medium
		Identify opportunities for collaboration between connected vehicle data capture activities and existing data programs.	Low
		Conduct annual review of regional mobility data programs to identify duplicate data collection and storage activities. Eliminate and replace with single source of data for specific data programs to ensure data is collected once and used many times.	High
		Identify applications that use expanding data sources, such as Strava.	Low
	Data Quality	Develop policy to define responsibilities for data quality assurance, including accuracy, timeliness, completeness, validity, coverage, and accessibility.	Low
		Adopt data quality standards for collection, processing, use, and reporting of mobility data.	Medium
		Require metadata for mobility data systems.	Low
		Document quality control procedures, including instructions on how to process data errors.	Medium
		Develop validation rules and allowable values for coded fields and incorporate these rules into data systems and data repositories. Use established validation rules to the greatest extent possible.	Low
	Data Standards	Develop and enforce data quality standards for travel time/speed data. Ideally, enforcement should be a collaborative effort whereby participants agree on holding each other accountable.	High
		Develop standard data template format to foster joint usage and collaboration on mobility data.	Medium
		Develop minimum regional standards for Bluetooth/GPS probe data	Low
		Ensure coordination with applicable national data standards.	High
		Develop policy to define responsibilities for supplying metadata, data dictionaries, and descriptive information for mobility data systems to facilitate the understanding, characteristics, and usage of data.	Medium
		Develop metadata guidelines to indicate data name, size, data type, where data is located, data ownership, update frequency, age of data, and how data can be used or integrated with other data sources.	Low
	Data Integration and Expandability	Leverage the Regional Integrated Transportation Information System (RITIS) as a tool for data integration. RITIS is available through Florida DOT District 7, so no procurement purchase is required. The MPO should facilitate the RITIS implementation effort from planning through fruition.	Medium
		Use common linear network to facilitate data sharing and integration.	High
		Develop procedures for attaching travel time data to roadway segments in the Multimodal Transportation Database.	High
		Determine improvements needed to the structure of the Multimodal Transportation Database to support data integration.	High
	Data Storage and Access	Understand stakeholders' business needs for mobility data access and sharing.	Medium
		Develop policy to define responsibilities for data storage, hosting, data retention/archival, and disposal.	Medium
		Develop policy to define data ownership and dissemination rights.	Medium
		Implement standard data sharing agreement with internal and external stakeholders.	High
Technology and Tools	Business Analysis Tools	Explore use of tools to integrate data from other systems and to enhance data sharing among regional stakeholders. These could include use of XML formats for sharing data, GPS technology for collecting and geocoding data location, and GIS tools for geographical display of data.	Medium
		Share published data in a centralized location such as the Multimodal Transportation Database, SharePoint, or open data portal that is accessible to internal and external stakeholders.	High
		Involve network/database administrators from partner agencies in development of shared data portal.	High
		Develop procedures for conducting analyses such as determining the average travel time and standard deviation during the PM peak on a typical weekday, or determining whether there is a correlation between travel time on arterials and fatality rates.	Medium
		Develop and implement training program on use of analysis tools.	Medium
Data Governance, Culture, and Collaboration	Data Governance	Implement a formal governance or collaboration framework.	High
		Identify and assign governance roles and responsibilities.	Medium
		Develop, maintain, and enforce a Data Governance Manual.	Medium
		Develop and publish a Data Catalog to increase awareness of mobility data availability.	High
		Develop and publish a Business Terms Glossary to define standard terminology for how mobility data is defined and used across the agency.	Medium
		Hold a Data Summit or conference to engage regional stakeholders and share ideas.	Low
		Identify resource needs.	Medium
	Collaboration	Identify datasets that can be openly shared.	High
		Determine which stakeholders are willing to engage in a data sharing agreement.	High
		Develop contract language for vendors to ensure data can be shared with other agencies.	Medium
	Data Privacy and Security	Establish and maintain security standards to secure data and protect privacy of individuals and contributing agencies.	High
		Clearly document policies, standards, and procedures and distribute to all staff responsible for collecting, maintaining, or distributing mobility data.	Medium
		With respect to accessing and using data with personal identifiable information (PII), stakeholders should be aware of the protections they have under 23 USC § 409 and are encouraged to seek further legal guidance with their attorneys.	Medium
		Further explore Privacy by Design as a way to address privacy concerns.	Low
	Performance Measures	Define performance indicators and implement a monitoring program to measure the success of the governance program. Performance indicators should measure program activities (i.e., outputs) and confirm the governance program is delivering results (i.e., outcomes). Output indicators quantify the activities of the Mobility Data Task Force and reflect the level of effort expended or scale/scope of activities. Outcome indicators quantify the effectiveness of the Coordination Group in terms of meeting its mission and stated goals. Example output and outcome indicators are provided in the Example Data Governance Manual in appendix G. Document the adopted measures in the Data Governance Manual. Note this reference to performance measures is not related to performance management requirements that are being implemented as pursuant to several rules codified in 23CFR part 490. In no way does this substitute for compliance under that rule. See FHWA TPM website for details related to 23CFR part 490.	Low
		Establish a communication protocol and plan for communicating performance measure results to executive level staff, Mobility Data Task Force, and data users/stakeholders.	Medium
	Risk Assessment	Conduct risk assessment to identify regional mobility data programs and current and potential risks associated with these programs (e.g., what would happen if there was a loss of data or data quality issues). A risk assessment matrix can be used to determine: 1) how much data is needed; 2) how accurate data should be; 3) what the refresh rate of the data should be; 4) who should have access to the data; and 5) potential risks of data loss.	Low
		Develop Risk Management Plan to address risks if they occur. Risk management practices should include disaster recovery procedures.	Low
	Knowledge Management	Develop and implement a Knowledge Management system for organizing, storing, and archiving knowledge regarding mobility data sets and workflow processes. This ensures lessons learned and experiences pertaining to mobility data are retained and archived as staff retire or leave the organization.	High

Step 6. Data Governance Processes And Documents

Data governance is defined as the "execution and enforcement of authority over the management of data assets and the performance of data management functions. […] Data governance promotes the understanding of data as a valuable asset to the organization and encourages the management of data from both a technical and business perspective." A lead agency should establish data governance processes and documents for its roadway travel mobility data programs, including developing a data governance model and defining roles and responsibilities to support data governance efforts at the agency.

One of the pilots adopted core data principles to guide mobility-related decisionmaking.

The following set of core data principles are recommended by the AASHTO Subcommittee on Data.² These data principles are also applicable for enterprise level governance efforts:

• Principle 1—VALUABLE: Data is an asset. Data is a core business asset that has value and is managed accordingly.
• Principle 2—AVAILABLE: Data is open, accessible, transparent, and shared. Access to data is critical to performing duties and functions. Data must be open and usable for diverse applications and open to all.
• Principle 3—RELIABLE: Data quality and extent is fit for a variety of applications. Data quality is acceptable and meets the needs for which it is intended.
• Principle 4—AUTHORIZED: Data is secure and compliant with regulations. Data is trustworthy and is safeguarded from unauthorized access, whether malicious, fraudulent, or erroneous.
• Principle 5—CLEAR: There is a common vocabulary and data definitions. Data dictionaries are developed and metadata established to maximize consistency and transparency of data across systems.
• Principle 6—EFFICIENT: Data is not duplicated. Data is collected once and used many times for many purposes.
• Principle 7—ACCOUNTABLE: Decisions maximize the benefit of data. Timely, relevant, high quality data are essential to maximize the utility of data for decisionmaking.

Data Governance Model. A data governance model depicts the relationship between an organization's strategic vision, mission, and goals for data, the agency's data programs, the various individuals/offices responsible for implementing data governance, and the users/stakeholders for the data programs, as shown in figure 3. In some cases, the Data Governance Board may work directly with the Data Stewards and Custodians.

Roles and Responsibilities for Data Governance. Table 6 defines the roles and responsibilities recommended to support a data governance model.

Table 6. Data governance roles and responsibilities.^{3, 4}

Role	Description	Responsibilities
Data Governance Council	Senior level managers across business areas of agency and typically includes Director of the IT Office or Division.	Establish the policies and procedures that shall be used in the collection and use of data and information, across the organization, and in support of the agency mission and goals.
Data Stewards	Individuals responsible for ensuring that the data which is collected, maintained, and used in the agency is managed according to policies established by the data governance board or council.	Identify and manage metadata. Identify and resolve data quality issues. Determine business and security needs of data. Communicate data quality issues to individuals that can influence change, as needed. Provide input to data analysis.
Data Business Owners	Individuals from the business side of the agency that are responsible for establishing the business requirements for the use of the data in their business area of the agency. They also may approve access to data applications supported by their business area. They may be internal or external to the agency.	Establish business rules for use of data in their business area. May approve access to applications supported by their business area.
Data Custodians	IT staff including IT security, network administrators, Database Administrators, server administrators, and Business area staff who are responsible for the "technical application" support for data systems. This may include application programmers and systems analysts who work in business areas other than the IT Office or Division.	Ensure safety and integrity of data in custody of IT. Implement application and data access controls appropriate for security classification. Provide reasonable safeguards for information resources.
Working Groups	Association of people who collect and provide data and establish business rules and processes for a specific data system. Working Groups may also include some of the internal and external stakeholders.	Provide assistance to the governing board in recommending the development of data products to meet business needs. Recommend procedures to the governing board for standards and procedures regarding collection, maintenance, and use of data programs and products within the agency. Recommend the technology tools for potential use to support data management at the agency.
Community of Interest	Association of people comprised of internal and external stakeholders who share a common interest as users of a data system.	Provide a focus for communicating business needs supported by data programs.

Figure 4 shows an example of a Data Governance framework from one of the pilots.

The lead agency should develop the following supporting documentation to define policies, standards, and procedures for data governance:

• Data Governance Manual. The manual serves as a centralized resource that formalizes data governance roles and responsibilities, data standards, policies, and procedures related to roadway travel mobility data. The manual also includes a data catalog with references to data definitions, data standards, metadata standards, data models, and contact information for IT and business subject matter experts. An example data governance manual is provided in appendix G.
• Data Catalog. The data catalog documents the roadway travel mobility data systems and the offices responsible for maintaining those systems. The catalog identifies the system of record for specific roadway travel mobility data sources, metadata about the data systems, and contact information for the data stewards and data custodians responsible for updating and maintaining the data.
• Business Terms Glossary. The business terms glossary defines how standard terminology for roadway travel mobility data (such as location) is defined and used across the agency. The glossary assists IT professionals in defining/using the data correctly when developing or enhancing data systems. An example glossary is provided in appendix H.

Step 7. Data Management Practices

A lead agency should implement effective data management policies and procedures for the collection, processing, analysis, and integration of roadway travel mobility data as part of its DBP. Data management is defined as the development, execution, and oversight of architectures, policies, practices, and procedures to manage an agency's information lifecycle needs pertaining to data collection, storage, security, data inventory, analysis, quality control, reporting, and visualization. Data management practices are necessary to acquire, update, describe, standardize, analyze, store and protect data to ensure it can be used.

Agencies should identify the data management practices, standards, and policies that will apply to the management of roadway travel mobility data in the DBP. The following aspects of data management should be considered:

• Data Acquisition. Define responsibilities for the collection, update and maintenance of data; for example identifying opportunities for collaboration between connected vehicle data capture activities and existing data programs; identify where duplicate data collection and storage should be eliminated. Data ownership/User rights need to be included here. This may also include investigating new data acquisition methods.
• Data Quality. Define data quality per governance standards; adopt data quality standards and metadata for the collection, processing, use, and reporting of roadway travel mobility data; document data quality procedures for each data system, with instructions on how to process data errors; and develop validation rules and allowable values for coded fields in data systems and repositories.
• Data Standards. Define metadata standards per governance standards for each type of data set (e.g., weather data, travel data, etc.), data dictionaries and descriptive information for data products; develop metadata guidelines to indicate update frequency, age of data, and specify how data can be used or integrated with other data sources; and coordinate with applicable data standards. Note that metadata standards are different from data format standards.
• Business Analysis Tools. Implement new/improved technology to integrate data from other systems and enhance sharing of data from these programs with other systems and stakeholders. The types of tools recommended could include the use of XML formats for sharing of data, GPS technology for collection of data and identifying the location of data collected, and GIS tools for geographical display of data.
• Data Privacy and Security. Ensure data privacy and security related to the data. For example, this could include coordinating with FHWA Connected Vehicle Senior Policy Working Group's recommendations related to security, ownership, and liability of connected vehicle data. Access to data that includes personally identifiable information (PII) was raised as a major issue during the pilot studies. Although the U.S. DOT is not in a position to provide legal counsel, lead agencies and stakeholders should be aware of the protections afford them under 23 USC § 409. It is recommended they seek further legal advice from their attorneys.
• Data Storage and Access. Define business requirements for data access, analysis and reporting; define responsibilities for data storage, hosting, data retention (archive), and disposal; define data ownership and dissemination rights; and explore methods to enhance access to information and data for the roadway travel mobility data. This includes developing Web-portals that are easily accessible by internal and external stakeholders for each of these programs to obtain data and information as needed.
• Traceability. Establish internal Data Working Groups for the roadway travel mobility data programs to examine data and information needs in the common business areas for each program, on a regular basis.
• Performance Measures. Identify measures of effectiveness (both qualitative and quantitative) and implement a monitoring program to measure the success of data coordination/data management activities and provide confirmation that the program is necessary and is effectively delivering results.
• Risk Assessment. Perform a risk assessment using a risk assessment matrix which identifies each data set used to support the roadway travel mobility data programs and current and potential risks (e.g., loss of data) associated with these programs.
• Knowledge Management. Develop and implement a knowledge management system to ensure that lessons learned and experiences pertaining to business operations within the organization are retained and archived as staff retire or leave the organization.

Step 8. Develop Implementation Roadmap

In this step, the lead agency should examine the improvement strategies identified in previous steps and assign logical steps and priority for implementation. Figure 5 shows an example implementation roadmap based on the pilot studies.

Step 9. Develop Data Business Plan

A lead agency should compile the results and documentation from previous steps into a single document. The DBP should include the following components:

• Chapter 1. Introduction—Describe the need, scope, objectives, and expected outcome of the DBP.
• Chapter 2. Stakeholder Outreach—Identify internal/external stakeholders and their involvement in development of the DBP.
• Chapter 3. Data and Gap Assessment—Provide a data inventory if available. Summarize assessment results and identified gaps. Summarize strategies/actions to improve data systems, data collection methods, data storage environments, data quality standards, data integration, data analysis, and analytical tools. The results of the assessment help prioritize data systems for enhancements or replacements to support mobility planning, operations, and performance measure activities.
• Chapter 4. Data Governance Framework—Explain how the lead agency will use data governance to support roadway travel mobility data. This section should include data principles, a customized data governance model to match the organizational structure of the DOT, and roles and responsibilities for management and governance of roadway travel mobility data. This section should also reference supporting documents including the Data Governance Manual, Data Catalog, and Business Terms Glossary.
• Chapter 5. Implementation Plan—Explain the steps the lead agency will take to implement the DBP.