7.4.2
Data Governance Practices Supporting TAM
Data governance practices can be implemented to support development of a valuable, reliable base of integrated information for TAM decision making.
A first step in data governance is to identify key decision points to be governed. These may include:
- Adopting common data definitions or standard code lists
- Adopting location referencing standards
- Adopting standard tools for field data collection
- Collecting new asset data to be included within an integrated asset management system
- Archiving or deleting existing data
- Modifying data elements for an existing TAM data source
- Adding new data layers to an enterprise GIS repository
- Adding new data marts to a data warehouse
- Adding new reports or controls to a BI environment
- Responding to an external request for data
It is best to take an incremental approach to setting up governance processes, starting with a few high impact areas that are aligned with what the agency is trying to achieve. For each of the selected decisions to be governed, think both about the criteria or guidelines to be followed as well as all the people who should be consulted or involved in making the decision.
TIP
Data governance practices should involve stakeholders responsible for collecting and analyzing the data, as well as those who will be using the data in decision making.
- Criteria and Guidelines: Developing guidelines for key decisions is a good way to institutionalize practices that reflect the agency’s goals for data. For example, some agencies have established “readiness checklists” that need to be completed before data can be added to an enterprise repository. These ensure (among other things) that a data owner or point of contact has been identified, that necessary metadata is provided, that a refresh cycle has been specified, and that the authoritative source system of record has been identified.
- Decision Making Process: Consider who should be involved in each of these decisions – who is responsible for making technical recommendations, who should be consulted, who has approval authority, and who needs to be informed about the decision. Define a process for resolving issues and conflicts; and a process for granting exceptions to established standards.
Agency data governance bodies can be responsible for adopting both guidelines and process flows impacting decisions that impact multiple business functions. If there are no existing governance bodies or if decisions to be governed are specific to TAM, a separate TAM data governance group can be established.
Keep in mind that the function of governance bodies is to make decisions. Use technical advisory groups, working groups or communities of interest to do the collaborative work required to develop standards or make recommendations about changes to data and systems.
Connecticut DOT
CTDOT established a data governance structure with an initial focus on creating a Transportation Enterprise Database (TED). The vision for the TED is to:
“Create an accessible transportation safety and asset data enterprise system where authoritative data sets are managed by data stewards and formatted for consumption and analysis in a manner that allows stakeholders to use tools that are both effective and meet their business needs.”
CTDOT’s Data Governance Structure is made up of:
- An Executive Oversight Committee, chaired by the agency Chief of Staff, with membership consisting of the agency’s bureau chiefs.
- A Data Governance Council, with members representing key agency functions including Policy and Planning, Asset Management, Engineering and Construction, Maintenance, Traffic, Safety Management, Finance and Administration, Public Transportation, and Information Technology. CTDOT uses consultants to facilitate.
- Data owners and stewards.
The initial charge of the Data Governance Council was to “Prioritize safety and asset data governance solutions to provide the foundational tools necessary to expand enterprise data participation across all disciplines within the agency.” The Data Council is responsible for:
- Identifying data being collected and maintained agency wide.
- Documenting data standards and coordinate development of new standards.
- Developing guidance for data dictionaries, user manuals, and training programs.
- Establishing quality control/quality assurance (QC/QA) processes.
- Facilitating the integration and interoperability of information between authoritative roadway inventory databases and the Department’s enterprise wide data system.
- Informing the Executive Committee of emerging data priorities and how they best might be addressed.
- Reporting to the Executive Oversight Committee as needed to make recommendations regarding data governance challenges or technology opportunities.
Data Owners:
- Have supervisory, administrative, and technical control over a dataset.
- Are responsible for the oversight of the collection, storage, maintenance, and implementation of business rules / managing its use including rules for how data will be exposed for general public consumption.
- Ensure access to the data asset is authorized and controlled.
Data Stewards are responsible for the management of data assets on a day to day basis in terms of content, update and data extract processes, data migration to TED and for the development of metadata. They ensure that:
- There are documents highlighting the origin and sources of authoritative data and completes each metadata element.
- Data has a collection and a maintenance cycle defined.
- Data quality processes are in place.
- Data is protected against unauthorized access or change.
Ohio DOT
Ohio DOT has established a standard process for adding a new asset to their inventory. As illustrated in the flowchart below, the process has three stages – (1) Asset Overview, where the request is submitted, evaluated, and approved, (2) Requirements, in which business and technical requirements for collecting and managing the new data are documented, and (3) Application Development, where the technology solution is developed either in-house (using standard tools), via contract (for custom development) or through acquisition of a commercial off-the-shelf (COTS) package.
As part of the TAM Audit Group workflow shown in the figure, ODOT has introduced over 693,000 active ancillary assets into their inventory.
Ohio DOT TAM Audit Group Workflow Diagram
Source: Ohio DOT. 2019