Data governance is exercising the appropriate authority and control over a data asset to ensure its integrity, quality, security, and availability to all qualified users. Proper governance offers many benefits including increased awareness of data holdings, improved organizational efficiency and productivity, more citizen-centered services, and better informed decision-making and evidence-based policymaking resulting in actionable intelligence. Governance increases the value of Commonwealth data assets by guiding and enabling its evolution from information to intelligence while promoting data discovery, exploration, integration, and sharing through the implementation of enterprise standards, policies, guidelines, and best practices.
On January 7, 2020, Governor Northam signed Executive Order 48 that established a data governance framework making Virginia a leader in data-driven policy, evidence-based decision-making, and outcome-based performance management. The primary goal of the framework is to help the Commonwealth be more responsive and make better, evidence-based decisions grounded in the data it collects and manages. The data governance framework includes the Virginia Data Commission, Executive Data Board, and a Data Governance Council.
Executive Data Board
Data Governance Council
Agency Data Officers
Data Management Technical Team
Data Domain Managers/Experts
Geospatial Information Officers
Information System Security Officers
Information System Security Managers
Data Scientists, Architects, Engineers, Analysts, and Consumers
The Virginia Data Commission is responsible for advising and assisting the Chief Data Officer in setting, planning, prioritizing, and reviewing data and outcome performance goals and objectives to improve operational efficiency, increase delivery of customer-centered services, and promote better outcomes for our constituents. The Commission's membership includes leaders from across state government charged with studying complex, multi-disciplinary problems, developing overarching goals that will help the Commonwealth address large scale issues, and making recommendations to the Governor identifying which state agencies are best positioned to implement the state's response.
The Executive Data Board consists of state agency executive leaders or their designees to review, approve, and adopt enterprise data policies, standards, guidelines, and best practices within their respective organizations to support the ongoing operations of the Commonwealth Data Trust. The Chief Data Officer works collaboratively with agency leaders to propose, discuss, and negotiate adoption of enterprise policies, standards, and best practices where full implementation may be impractical, costly, or impossible for some state agencies. Respect, trust, flexibility, and consideration are key to this relationship. In addition, the Board is responsible for translating state goals developed by the Virginia Data Commission into agency performance targets that will help the state meet its identified objectives. It takes a team effort to fully address the complex issues facing Virginia today. No single state agency can have the same impact as a collective of agencies working together towards a common goal.
The Data Governance Council is composed of agency data owners having a thorough understanding of how the data they collect supports the organization's mission. These individuals make decisions about who gets access to the data available through the Commonwealth Data Trust. They also work with the Chief Data Officer to identify, develop, and recommend policies, standards, guidelines, and best practices that will improve data trust operations. In addition to operational oversight of the Commonwealth Data Trust, the Council is responsible for identifying state agency data assets that can be used to develop the metrics and measures needed to monitor the agency's success towards meeting its performance targets.
The Data Stewards Group is the technical arm of the governance framework. Group members are technical staff of trust member organizations that usually report to their respective data owner on the Data Governance Council. These individuals are responsible for implementing the access decisions made by their organization's data owner. They are also responsible for monitoring access to their data systems ensuring queries are executed only by authorized individuals on approved data assets. This group is an important part of the governance framework by highlighting some of the technical issues associated with data sharing, privacy, and security.
Data Value Chain
The data value chain is the evolution of data from information to intelligence within an organization. It describes the various forms data can take as organizational units transform it to fit their needs. Some have described “data” as the new “oil,” but that’s based on a flawed premise. Oil decreases in value once it’s used, data does not. Data increases in value the more it’s used and should be considered a non-depleting resource. Leveraging the data value chain supports a virtuous cycle of continuous improvement when knowledge gaps and data errors are identified and corrected.
The figure below describes the process associated with the data value chain. Data is collected by an organization for a specific, usually operational, purpose. There’s inherent value in the data or the bits and bytes stored within a database or information system due to the cost associated with its collection, storage, and management. However, it isn’t until the data is interpreted that it becomes information. The interpretation of data is usually within a specific context or domain like transportation, education, health, environment, etc. That is to say, the person interpreting the data is usually looking at it from a particular, very specific, perspective. This perspective provides the constraints under which the interpretation applies and the information generated is limited (in most cases) to that domain.
Domain specialists and experts assimilate the information identifying the patterns, trends, and mechanisms associated with the occurrence of the real-world events the data represents creating knowledge. Knowledge can be integrated into the decision-making process of the organization creating intelligence. Intelligence supports better informed decision-making and evidence-based policymaking resulting in actions making government agencies more efficient, providing better services, and improving the lives of citizens across the Commonwealth.
Our data strategy has four primary components: Governance, Architecture, Management, and Intelligence. Governance, as mentioned above, is the foundational component that drives the data architecture. While governance is the people-based processes exercising authority and control, architecture is the blueprint or model of how data flows through the organization as it is collected, stored, processed, integrated, and analyzed. It is the design process guiding the implementation of appropriate data management. Management is where the “rubber meets the road.” This is the component where networks are created, systems are developed, and standards are implemented. The data management process supports data quality assessments, exploratory data analysis, data analytics, machine learning, and business or mission intelligence. Without appropriate and consistent data management, data analysts, specialists, and scientists would have to individually document, curate, transfer, manipulate, and transform data prior to conducting any form of analysis. You just can’t skip data management. It’s an inherent part of every data analytics project and it is best done as an enterprise service and not an ad-hoc or project-based endeavor. Completing the feedback loop, results generated by data analytics or intelligence projects inform the data governance layer by identifying flaws in the architecture, gaps in management, and/or data errors in the analytics, making the organization smarter.
Underlying the 4 components are 6 principles that guide the implementation of the data strategy. These principles dictate that data is:
- used to support mission goals;
- interpreted, analyzed, and assimilated to support actionable decisions;
- standardized to promote interoperability and integration;
- managed to maintain quality, integrity, and reliability;
- accessible with appropriate security controls; and
- disseminated to promote reuse
Within the Commonwealth, Data Governance is the primary domain of the Chief Data Officer, while the Architecture, Management, and Intelligence components fall within the Chief Information Officer’s responsibilities. The CDO supports the CIO as necessary in matters related to the creation, storage, dissemination, and analysis of data. We recognize that good analytics depends on governed data and data governance is a team sport.