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The Data Governance Framework Tool is one of a suite of applied Community Well-being tools developed by SGIGs to form part of the online Data Governance and Management toolkit. The Tool is an overarching framework describing and providing guidance with respect to the component parts of a data governance program.

This page presents a summary of the key highlights of the Data Governance Framework Tool, including a webinar for further guidance. The full tool contains several fictional scenarios and further information to guide SGIGs toward an effective data governance program that empowers SGIGs to harness the power of data to inform advocacy, decision-making, and investment while also protecting collective and individual rights to privacy and confidentiality. It is available for download as a PDF:

What is data governance?

Data governance is the system and structure through which the benefits of data can directly and consistently contribute to effective, efficient, and responsive governance, from planning to policy development to programming and operational decisions.

A data governance program:

  • ensures that data are understood, trusted and used appropriately;
  • supports the people who collect, manage and use data to understand how those data add value to their work and the SGIG’s overall objectives;
  • and allows SGIGs to minimize risks around the data they hold, while leveraging the maximum benefit from it.

Summary of the Data Governance Framework Tool

The Data Governance Framework Tool is intended to support SGIGs to continuously improve their data governance programs, recognizing that no government or organization has a perfect data governance program – data governance is about continuous improvement, not how to get everything “right” all at once. While drawing upon the best practices and available expertise in data governance worldwide, this Framework is also designed to maintain the uniqueness of Indigenous governments, rooted in the right of Indigenous data sovereignty and responsive to the unique contexts of Indigenous peoples and governments. It will be an evergreen document, updated through time in recognition of the evolving field of data governance among Indigenous governments and beyond.

This Framework is organized around a visual of an overall data governance program, highlighting the various component parts and their interrelationships. Each component part of this Framework is defined, its importance explained, and key considerations and strategies to address those considerations are described. Scenarios are used throughout to bring data governance to life.

Overview of a Data Governance Program

The Data Governance Framework visual depicts the various factors or aspects involved in a data governance program. The diagram is presented using circles, layers, and arrows to represent the highly interconnected nature of its concepts and component parts. It is reminiscent of a drum which represents balance and equality, wholeness and connection.

Essentially, this visual is a conceptual starting point that must be adapted to present needs, realities, preferences, and norms. A data governance framework and program is more successful when adjusted to reflect the terms and approaches that resonate with the SGIG’s culture — socially and organizationally.

Core purpose

At the centre of the diagram is the core purpose of an SGIG’s data governance program: to express data sovereignty through ownership, use, and protection of quality data. Arrows radiate from this core purpose statement, illustrating its importance as a touchstone that grounds all aspects of a data governance program.

Core components

The four quadrants surrounding the centre of the program represent the core components of a data governance program:

  • Vision, goals, principles: Establishing the overarching thought leadership and guidance for data governance, specifically through a clear strategic statement describing the desired future state of data governance, a set of high-level statements describing how that future state will be achieved, and the key cross-cutting factors that guide data governance decision-making.
  • Laws, policies, procedures: Articulating the “rules” of data governance – the expectations and requirements that describe how the purposes, vision, goals, and principles of a data governance program are defined and are to be carried out.
  • Roles, responsibilities, processes: Describing the personnel and patterns that support accountability for data governance, such as the responsibilities of key staff positions, and any working structure (e.g. committee) empowered to make decisions related to data.
  • Monitoring, reporting, evaluation: Defining how it is known that the data governance program is working and what needs to be strengthened, such as through establishing and reporting against metrics and processes and acting upon results to achieve improvement.

Data life cycle

The arrows surrounding the core components of a data governance program represent the data life cycle. All data will be at some stage in this data life cycle, and possibly in multiple stages at once (for example, stewarding data would be taking place as data are also being gathered or used). All four components of a data governance program should consider and provide for all four stages of the data life cycle:

  • Gather: Acquiring data, such as through surveys or primary data collection, or through repatriating data held by others.
  • Steward: Holding and caretaking data, including security and confidentiality.
  • Use: Working with data to answer questions, inform decisions, and measure progress.
  • Archive: Disposing or permanently preserving data.

Influencing factors

The outer circle represents four internal and external factors that shape (for example, enable or constrain the success of) the operation and performance of a data governance program.

These are:

  • People: The success of any and all aspects of a data governance program rests upon the actions of individual people and their knowledge, buy-in, and competencies/skills.
  • Systems: The efficiency and effectiveness of a data governance program can be enhanced by proactive planning, and design and implementation of technology solutions and routine processes and workflows.
  • Organization: Organizational culture – customarily strongly associated with the views and behaviour of organizational leadership – drives the perceived value and relative priority of data within an organization and the priorities and norms for a data governance program within and across the SGIG.
  • Partners: A data governance program can be interrelated with organizations such as academic institutions, or federal, provincial, or territorial governments which have data belonging or of interest to the SGIG. This relationship may be codified through protocols or information-sharing agreements.


Arrows directed inward from this ring are illustrative of how critical this internal and external context is in shaping, informing, enabling, and constraining all other aspects of the data governance program.

Although the diagram represents a comprehensive picture of data governance, an SGIG can focus on different aspects of the diagram at different times, depending on their needs, priorities, and capacity. It is easy to “overbuild” a data governance program by investing more time and resources than necessary, which tends to mystify, impede, and limit the use of data. Instead, many choices can be made about what is “good enough” to meet legal, ethical, and technical requirements. It is essential to scale a data governance program to the SGIG’s unique setting and circumstances. No government or organization has a perfect data governance program – this framework supports continuous improvement, not how to get everything “right” all at once.

Downloadable documents

Data Governance Framework Tool