Implementing Data Governance at Transportation Agencies: Volume 1: Implementation Guide (2024)
Chapter: 1 About this Guide
1. About this Guide
What is Data Governance?
Every transportation agency has governance in place that defines who in the agency sets direction, provides oversight, and makes decisions for different aspects of the agency’s operations. Governance in a public agency is carried out through documented responsibilities and accountabilities for agency managers; chartering standing committees or groups to serve in advisory or decision making roles; adopting policies and procedures that specify what agency staff must do and how, and establishing processes for internal controls, auditing and reporting. Governance can be viewed as an orchestration function, making sure that each part of the organization understands their part and works together for a common purpose.
Data governance is “a set of practices and guidelines that define the loci of accountability and responsibility related to data within the organization. These guidelines support the organization’s business model through generating and consuming data.”
- MIT Sloan Management Review [1]
Similarly, data governance orchestrates data-related activities in an organization to accomplish business objectives. It encompasses strategy, guidance, and decision-making processes for how agencies collect, purchase, document, store, protect, access, share, and ensure quality of their data. Implementing data governance moves an agency from ad-hoc and fragmented ways of managing data to more consistent and repeatable processes. This reduces risks of data loss, misuse, and under-utilization and enables agencies to use their data to make better decisions that support agency goals.
Data governance is best implemented at the agency-wide level for maximum impact and benefit – an enterprise approach is needed to overcome barriers to data sharing and integration across organizational silos. However, agencies can begin with a focus on individual key data programs (for example, safety data or geospatial data). Data governance requires a strong partnership between business and information technology (IT) leaders in an agency.
Data Governance is not the same as Data Management
Data Governance is often confused with Data Mangement. They are related but not the same.
Data Management encompasses activities to curate, collect, document, clean, store, protect, share, deliver, and archive or delete data.
Data Governance is a strategy and oversight function for Data Management. It establishes policies, decision-making roles and processes and standards that guide management of data.
This Guide focuses on Data Governance - it touches on but does not cover the nuts and bolts of Data Management.
Implementing data governance generally involves:
- Classifying Agency Data to define the scope of what is to be governed and identify sensitive data to be protected;
- Designating Decision-Making Roles and Responsibilities (for groups and individuals) – to establish accountability and set expectations for how certain data-related decisions are made, how issues are resolved and how data management and governance processes are to be carried out and tracked;
- Defining and Adopting Standards – to build consistency in data formats and structures, as well as in templates used to document data;
- Establishing Policies and Guidance – to define agency expectations for practices, processes and procedures to be followed prior to collecting or acquiring data, modifying existing data, sharing data, and publishing data;
- Implementing Tools – to catalog agency data, produce and maintain data documentation, manage business glossaries, define and apply business rules for data, and manage data workflows; and
- Communicating, Training and Managing Change – to build awareness and facilitate adoption of the agency’s data-related policies and practices.
Why a Guide on Data Governance for Transportation Agencies?
Transportation agencies produce and consume large quantities of data and are seeking to better use their data to improve safety, mobility, accessibility, equity and efficiency. Many transportation data programs are mature and have well-functioning processes for collection, processing and reporting. However, agencies are constantly challenged to integrate data across disparate sources, reduce data duplication and inconsistencies, improve data quality and trust, ensure protection of private and sensitive data, and respond to evolving expectations for data sharing (with partners and the general public). Some agencies face new state-level requirements related to sharing and managing data. Data governance enables transportation agencies to set organizational expectations for how data are managed and equips them to respond to changing needs and opportunities.
Data Governance and Artificial Intelligence (AI)
Data governance is key to successful application of AI techniques that can tap into the expanding pool of available data to provide new insights for improving safety, mobility, and organizational effectiveness. Data governance can facilitate:
- Making the right data availble to train machine learning (ML) models – accessible, authoritative, quality-checked, and unbiased.
- Collaboration across data scientists, data owners and managers, engineers, and other stakeholders needed to create, validate and ensure appropriate use of models.
- Identifying and managing risks associated with use of AI models and ensure compliance with applicable data privacy, security and ethical use policies.
Some transportation agencies have active data governance programs while others are at early stages or have yet to begin. Some have seen their efforts stall. This Guide was created so that agencies at various stages of implementing data governance can benefit from the lessons learned and experience of peer agencies.
There are many books and guidance documents with a wealth of information on data governance techniques, applicable for both public and private sector organizations. This Guide distills information from these existing references that is most relevant for transportation agencies. It is not intended to be a comprehensive or all-encompassing reference on data governance. The Guide provides references for those who want to explore various aspects of data governance in greater depth.
Who is this Guide For?
This Guide is intended for people engaged in sponsoring or implementing data governance activities at state, regional and local transportation agencies. This includes:
- Members of the agency leadership team (e.g., deputy directors or division administrators);
- Agency data governance leads and staff;
- Staff that manage or oversee data programs;
- Staff responsible for day-to-day data management tasks; and
- Staff whose jobs involve substantial data compilation or analysis tasks.
The Guide may also be helpful to state-level data and information management professionals that work with data beyond the limits of a DOT, such as state Chief Information Officers (CIOs), Chief Data Officers (CDOs) and their staff.
