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.
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.
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.
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.
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.
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:
- 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.
(Source: Cambridge Systematics, Inc.)
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.
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.
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.
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.
(Source: Cambridge Systematics, Inc.)
Roles and Responsibilities for Data Governance. Table 6 defines the roles and responsibilities recommended to support a data governance model.
|Data Governance Council||Senior level managers across business areas of agency and typically includes Director of the IT Office or Division.||
|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.||
|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.
|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.||
|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.||
|Community of Interest||Association of people comprised of internal and external stakeholders who share a common interest as users of a data system.||
Figure 4 shows an example of a Data Governance framework from one of the pilots.
(Source: Cambridge Systematics, Inc.)
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.
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.
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.
(Source: Cambridge Systematics, Inc.)
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.
2 AASHTO Subcommittee on Data, Data Subcommittee Efforts on Core Data Principles Web site, https://data.transportation.org/aashto-core-data-principles/. [ Return to Note 2 ]
3 NCHRP 666: Target-Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies, Volume II: Guide for Target-Setting and Data Management, 2010. [ Return to Note 3 ]
4 Data Governance, Standards, and Knowledge Management, Alaska Department of Transportation and Public Facilities (ADOT&PF), 2009, Appendix B—Kansas Department of Education Roles and Responsibilities and Appendix C—Data Governance Manual. [ Return to Note 4 ]