DND/CAF Data Governance Framework

On this page

• 1. Introduction
• 2. Charter
  • 2.1 Scope
  • 2.2 Principles
  • 2.3 Outcomes
• 3. Operating Model and Accountabilities for Data Governance
  • 3.1 Operating Model
  • 3.2 Data Governance, Data Stewardship, and Data Management Activities
  • 3.3 Data Domains
  • 3.4 Tiered Governance Structure
• 4. Oversight
  • 4.1 ADM(Data, Innovation, Analytics)
    • 4.1.1.0 Role of ADM(DIA)
    • 4.1.1.1 Scope of ADM(DIA)’s Data Governance Responsibilities
    • 4.1.1.2 Data Governance Activities of ADM(DIA)
    • 4.1.1.3 ADM(DIA)’s Relationship with Other Data-Related L1 Roles
  • 4.2 The Defence Data Management Board (DDMB)
• 5. Planning
  • 5.1 Director General, Data Program Oversight Committee (DG DPO)
  • 5.2 Within ADM(DIA)
    • 5.2.1.0 The Data Governance Office (DGO)
    • 5.2.1.1 Role of the Data Governance Manager
• 5.3 Within ADM(IM)
  • 5.3.1.0 Role of the Information System Design Authority (ISDA)

• 6. Execution
  • 6.2 Implementation Approach
    • 6.2.1.0 Overview
    • 6.2.2.0 Step-by-Step
  • 6.3 Working Groups
    • 6.3.1.0 Overview
    • 6.3.2.0 Data Governance Working Group (DGWG)
    • 6.3.3.0 Data Stewardship Working Groups (DSWGs)
  • 6.4 Data Stewardship Model
    • 6.4.1.0 Overview
    • 6.4.2.0 The Chief Data Officer (CDO)
    • 6.4.3.0 Role of the Data Governors
    • 6.4.3.1 Scope of the Data Governors
    • 6.4.3.2 Responsibilities of the Data Governors
    • 6.4.3.3 Data Governor’s Relationships with Other Data Roles
    • 6.4.4.0 Role of the Data Officer
    • 6.4.4.1 Scope of Data Officer Role
    • 6.4.4.2 Responsibilities of the Data Officer
    • 6.4.4.3 Data Officer’s Relationships with Other Data Roles
    • 6.4.5.0 Role of the Data Domain Steward
    • 6.4.5.1 Scope of Data Domain Steward
    • 6.4.5.2 Responsibilities of Data Domain Steward
    • 6.4.5.3 Data Domain Steward’s Relationships with Other Data Roles
    • 6.4.6.0 Role of the Data Steward
    • 6.4.6.1 Scope of the Data Steward
    • 6.4.6.2 Responsibilities of the Data Steward
    • 6.4.6.3 Data Steward’s Relationship with Other Data Roles
    • 6.4.7.0 Role of the Data Custodian
    • 6.4.7.1 Scope of the Data Custodian
    • 6.4.7.2 Responsibilities of the Data Custodian
    • 6.4.7.3 Data Custodian’s Relationship with Other Data Roles
  • 6.5 Supporting Roles
    • 6.5.1.0 Overview
    • 6.5.2.0 Analytics Support Centre, Managers’ Coordination Committee (ASC MCC)
    • 6.5.3.0 Data Citizen
    • 6.5.4.0 Data Advisor
    • 6.5.5.0 Data Consumer
    • 6.5.6.0 Data Producer
    • 6.5.7.0 Business Data Specialist
    • 6.5.8.0 Data Professional
• Appendix A: References
• Appendix B: Definitions
• Appendix C: L1 Data Considerations
• Appendix D: Out of Scope
• Appendix E: Contributors
• Appendix F: Citations

1. Introduction

With the release of Canada’s Defence Policy: Strong, Secure, Engaged in 2017, it is acknowledged that modern militaries increasingly need to rely on networks and data to plan and carry out missions. The Department of National Defence and Canadian Armed Forces (DND/CAF) is therefore in the process of modernizing the business of defence, and with it, providing a greater focus on digital and data-driven ways of working. Well-governed data is foundational to the enablement of the integration, transformation, aggregation, and consumption of large amounts of data, and introduces the potential for data-driven innovations, such as artificial intelligence (AI), to be deployed at scale.

The Assistant Deputy Minister (Data, Innovation, Analytics) has been tasked by the Deputy Minister and Chief of Defence Staff with the development and implementation of a ‘robust data governance framework’^{Footnote 1}. Currently, DND/CAF is creating petabytes of data with no framework on how to govern, use or exploit this strategic asset^{Footnote 2}, thereby limiting the potential benefits that can be realized. DND/CAF has an opportunity to change this through the implementation of the DND/CAF Data Strategy, and the development and implementation of the Data Governance Framework (DGF) that supports operations and provides the potential for future data-driven activities^{Footnote 3} to expedite access to data and to support the operationalization of DND/CAF priorities.

The Data Governance Framework takes the key elements of the DND/CAF Data Strategy and creates a consistent, adaptable structure for data governance within DND/CAF. A key aspect of this framework is transitioning the department from accessing data on a ‘need to know’ basis to one that is focused on a ‘need to share’ basis through data integration, orchestration, and interoperability. In this way, DND/CAF has an opportunity to fully optimize the data at its disposal as a strategic asset to support military operations.

The implementation of the Data Governance Framework will enable a change in the conversation, from L1s ‘owning’ data, to one in which all those who collect, access, manage, and disseminates data understand that there is shared responsibility for ensuring that data are accessible, secure, trusted, and managed ethically^{Footnote 4}. This framework will support the reduction of data silos, movement towards trusted authoritative resources, and production of good quality data that can inform the development of AI and other data-driven solutions.

The Data Governance Framework builds on existing organizational practices and formalizes them so that the structure clearly delineates who is responsible for what activity. As this framework is promulgated, there will be some activities implemented immediately and others implemented in the medium to long-term. For example, the governance committees already exist, and Data Advisors already offer advice and guidance on an ‘as required basis’. However, as L1s formally adopt the role of Data Governors and Data Officers, there will be a need to identify specific stewards to oversee, monitor, and enforce compliance with enterprise-wide data policies, standards, and guidelines. A viable data governance structure will complement the IT infrastructure to support access to data across DND/CAF.

The success of this Data Governance Framework will be measured by a clear set of metrics^{Footnote 5}. Through performance measurement, it should become clear which parts of the Data Governance Framework need to improve, change, or pivot to meet the evolving needs of DND/CAF priorities. Sharing performance metrics across DND/CAF will enable L1 organizations to identify best practices and will promote a culture of internal transparency, accountability, and the use of data assets to support the business of defence.

2. Charter

2.1 Scope

This framework identifies the data governance principles, operating model, execution, planning and oversight as well as a Data Stewardship Model which defines the roles and responsibilities of the following individuals and groups:

• The Chief Data Officer (CDO)
• Data Governors
• Data Officers
• Data Domain Stewards
• Data Stewards
• Data Custodians (an IM/IT function)
• Data Citizens
• Data Advisors
• Data Consumers
• Business Data Specialists
• Data Professionals
• Data Producers
• ADM(IM)
• ADM(DIA)

2.2 Principles

Following the principles established by the DND/CAF Data Strategy, DND/CAF will ensure that:

• Data is managed as a shared asset. DND employees and CAF members are stewards of data; responsible for ensuring that data are collected, managed, and used to the benefit of DND/CAF, the Government of Canada, and Canadians.
• Data is accessible. DND/CAF’s data holdings are accessible and available to those who need them.^{Footnote 6}
• The data governance model is adaptive. The framework enables DND/CAF to have the necessary structure to support the business of defence and considers the needs of L1s to access data across the department while ensuring appropriate protection of sensitive/classified information.
• The Data Domains are managed through a stewardship model; an identified L1 does not ‘own’ the data, but instead, is accountable for the stewardship of that data for the benefit of all other L1s.
• Data governance augments and supports data analytics, business intelligence, and data science consistently across DND/CAF.
• Data governance applies to all systems, across all networks managed by DND/CAF.

2.3 Outcomes

In developing and implementing a ‘robust data governance structure’^{Footnote 7} that supports the modernization of the business of defence, the outcomes are objectives that are achieved through the implementation of the Data Governance Framework. The Data Governance Framework implementation is not itself the desired outcome, but rather it is the vehicle toward the ultimate achievement of these outcomes. The expected outcomes following the implementation of the Data Governance Framework are:

• Develop and implement data stewardship practices across DND/CAF
• Improve data management processes and activities
• Make data more accessible for Data Consumers
• Evaluate and recommend data tools for users with varying data competencies
• Foster a more literate data culture
• Improve data management, access, and quality standards to enable trusted, informed decision-making
• Exploit data at the tactical edge to support mission success^{Footnote 8Footnote 9Footnote 10}
• A common, integrated view across disparate systems to allow for more efficient and integrated operational activities^{Footnote 11}
• Reduce data duplication and system complexity, and thereby increase value-for-money from outgoing financial investment to support operational readiness and base sustainability; and,
• Minimize risk of data and privacy breaches

3. Operating Model and Accountabilities for Data Governance

3.1 Operating Model

In common with the culture of DND/CAF, data governance is a federated, hub and spoke model. It leverages existing authorities to formalise accountabilities and responsibilities for managing data. It introduces the Data Stewardship Model which will improve access and shareability of the data held within systems, and enable Data Consumers to receive usable, accurate and timely data.

ADM(DIA) as the functional authority is responsible for providing strategic direction on data management and analytics, as well as being responsible for disseminating best practices, standards, and recommended tools to support data quality, integration, and interoperability^{Footnote 12}. L1s are responsible for amplifying this approach locally and collaborating with ADM(DIA) and other L1s on the use and promotion of use of DND/CAF data^{Footnote 13}. The Data Governance Framework operates in parallel to the Analytics in DND/CAF: Vision and Guiding Principles^{Footnote 14} document, which together will ensure and provide the foundation for DND/CAF data management frameworks so that the management of data and analytics occurs in a holistic fashion.

3.2 Data Governance, Data Stewardship, and Data Management Activities

Data governance is the lynchpin that provides the department with the essential foundation required to facilitate its data management activities. Data governance is defined as the ‘logical structure for classifying, organizing, and communicating complex activities involved in making decisions about and taking action on enterprise data’^{Footnote 15}. The clear identification of roles and responsibilities and the introduction of accountability of the data are large contributors to this essential foundation. A key deliverable from this activity is the development and implementation of data stewardship. In the DND/CAF Data Strategy^{Footnote 16}, under the future state of Data Management pillar, it envisions that formalized data governance incorporates well-defined data stewardship roles and establishes a network of data stewards. Data stewardship is defined as the ‘formalization of accountability for the management of data assets on behalf of others and in the best interests of the organization’.

From this Data Governance Framework and the embedded Data Stewardship Model, data management activities are then established to support the data continuum^{Footnote 17}. These data management activities align with the following Knowledge Areas^{Footnote 18}:

• Data Architecture
• Data Integration and Interoperability
• Data Modeling and Design
• Data Quality
• Data Security^{Footnote 19}
• Data Storage and Operations
• Data Warehousing and Business Intelligence
• Document and Content Management^{Footnote 20}
• Metadata Management
• Reference and Master Data Management

Figure 1: DAMA DMBoK Knowledge Area Wheel

The Data management activities are shared across the department, with ADM(DIA) assuming the functional authority for the strategic management of data. A breakdown of roles and responsibilities for specific data management activities has been identified in the DND/CAF Data Strategy and will be further amplified within the Data Strategy Implementation Plan (DSIP).

Figure 2: DND/CAF Data Domains

3.3 Data Domains

Data Domains are grouped by function. The current landscape of Defence Data Domains is depicted in the image (Figure 2). There are three categories of Data Domains across DND/CAF: Corporate, Common and Operational. Corporate L1s of DND support the Operational L1s of CAF to pursue the business of defence. Corporate L1s interact with Corporate or Common Data Domains, whereas Operational L1s interact with Operational or Common Data Domains. The list of Data Domains will remain evergreen and expansive as Data Officers discover the breadth of their environment and new business requirements or activities are introduced. Each L1 may interact with one or several Data Domains and can fulfill different roles within those Data Domains. For example, they may be stewards, advisors, consumers, or producers of the data within any given Data Domain. The nature of each of those roles bear different sets of responsibilities which are described in this document.

Data Domains can each have their own policies, sets of standards or best practices, and unique processes or tools for their data. Data Advisors of DND/CAF provide communications and insight on these, and L1 Data Officers must ensure their Data Domain Stewards are able to provide sufficient opportunity for guidance and awareness to their working-level stewards to ensure compliance. Where a Data Domain exists across multiple L1s, care should be taken by Data Domain Stewards, they must address any barriers with their Data Officer to promote horizontal alignment across DND/CAF by encouraging the engagement of other L1s and ADM(DIA).

3.4 Tiered Governance Structure

Following the principle of adaptive data governance, data is managed through a tiered governance structure that ranges from a strategic enterprise approach at the Defence Data Management Board (DDMB), down to working levels throughout all L1s.

Figure 3: Data Governance Structure

4. Oversight

4.1 ADM(Data, Innovation, Analytics)

4.1.1.0 Role of ADM(DIA)

ADM(DIA) is the functional authority for data management, data governance, analytics, data-enabled business transformation and certain data-driven applications such as artificial intelligence applications^{Footnote 21}, and is also the departmental service lead under the Treasury Board Secretariat implementation of the Policy on Service and Digital.^{Footnote 22} ADM(DIA) is responsible for providing departmental leadership, direction, and services in implementing these activities for and on behalf of the DND/CAF. ADM(DIA) sets direction on data management and analytics through the Data Governance Framework^{Footnote 23} and the DAOD 6500 series on Data Management and Analytics. Data management frameworks activities will be established from the foundation and structure set out in the Data Governance Framework. In some circumstances, there will be collaboration with other L1s on the development of other DAODs on shared interests, for example, the potential to develop a policy instrument on metadata management.

Figure 4: Authority of ADM(DIA)

4.1.1.1 Scope of ADM(DIA)’s Data Governance Responsibilities

For the purposes of this framework, the ADM(DIA) is responsible for the following:

• Establishing strategic leadership, governance, sponsorship, and guidance to DND/CAF senior leaders to successfully transition DND/CAF to a data-driven organization that manages data as strategic assets to support decision-making and the business of defence.
• Issuing directives, standards, frameworks and guidelines on data management and analytics, and overseeing their compliance, monitoring, and reporting to the Deputy Minister and Chief of Defence Staff (see Figure 3).
• Approving and overseeing plans and programmes pertaining to data management, analytics, certain elements of artificial intelligence, data-driven innovation, and coordination of public-facing and internal enterprise services and the data that supports them.
• Providing security, trust, and an understanding of all L1 data among its stakeholders, especially as more data sources and assets come on board.

4.1.1.2 Data Governance Activities of ADM(DIA)

The specific activities that ADM(DIA) will undertake are as follows:

• Lead on the strategic direction on collection, use, and management of data within DND/CAF.
• Develop and maintain controls on data quality and interoperability to effectively manage departmental risk associated with the use of data and analytics.
• Initiate a plan to address the issues of data sharing for interoperability with allies and the Five Eyes (FVEY) community.
• Collaborate with L1s to create controls for the appropriate management and protection of data assets, including data held within third party owned and operated applications^{Footnote 24}.
• Foster the creation of a data-driven culture across the enterprise.
• Establish strategic directions on data literacy and a culture of evidence-based decision making.
• Direct and sponsor departmental-wide data and analytics initiatives, and support L1s as they move towards data-driven decision-making and modernizing the business of defence.

4.1.1.3 ADM(DIA)’s Relationship with Other Data-Related L1 Roles

The key relationships of ADM(DIA) include:

• Chief Information Officer of ADM(IM) – work collaboratively on the integrated management of services, data, information management, information technology, and cyber security following the direction within Treasury Board’s Policy and Directive on Service and Digital, and the Digital Operations Strategic Priorities.
• Data Governors (Representatives on DDMB) – works collaboratively in setting, approving, and reviewing DAODs, standards and guidelines, and establishing scope of data governance and prioritisation of Data Domains^{Footnote 25}.
• Within L1s – serve as champions and advocates for data management, analytics, and the utilisation of artificial intelligence/machine learning. Collect input on role of data to support key L1 initiatives and gain understanding of and support for data and analytics activities.
• Data Advisors – works collaboratively on issues of data privacy, security, interpretation of current legislation impacting data related issues, information management, and IT infrastructure.
• Data Officers – communicate the DAOD on Data Management and Analytics, provides feedback and data to guide policy and best practices over time; and provide explicit direction to Data Officer and Data Domain Stewards.
• Other Chief Data Officers in Government of Canada Departments – work collaboratively to gain common understanding of cross-departmental challenges, solutions and potential opportunities for enterprise data management and analytics.

4.2 The Defence Data Management Board (DDMB)

The Defence Data Management Board (DDMB) is the most senior governance body convened by the ADM (DIA) to support its functional authorities in data management, analytics, data-centric innovation, and data-enabled business transformation. DDMB considers, shapes, directs, and monitors enterprise-wide data-driven transformation. DDMB also provides guidance and direction on Defence priorities, risks and issues pertaining to data and analytics to ensure that data are leveraged in all aspects of Defence programs, enhancing our defence capabilities and decision-making, and providing an information advantage during military operations.^{Footnote 26}

5. Planning

5.1 Director General, Data Program Oversight Committee (DG DPO)

The role of the Committee is described in the Terms of Reference^{Footnote 27}.

The Director General, Data Program Oversight Committee (DG DPO) has been established to provide strategic direction and oversight on the delivery of the DND/CAF Data Strategy, and its implementation plan.

DG DPO supports and aligns with Defence Data Management Board (DDMB) as required.

• The DG DPO provides a forum for reporting on progress and issues related to data quality, analytics, data governance and stewardship, and data management to support the objectives and outcomes of the DND/CAF Data Strategy.
• The DG DPO can create working groups as needed covering key areas within its scope, such as the Data Governance Working Group (DGWG).
• DG DPO provides central coordination, negotiation, and reviewing / vetting recommendations from the Analytics Support Centre – Managers Coordination Committee, and Data Governance Working Group, and as needed makes recommendations to DDMB on the DND / CAF efforts in data and digitization.

5.2 Within ADM(DIA)

5.2.1.0 The Data Governance Office (DGO)

The Data Governance Office (DGO) supports ADM(DIA) and DND/CAF by promoting and monitoring compliance to standards, policies, administrative orders, and directives concerning data governance and data management. It provides the platform to enable data stewards and facilitate collaboration across the organization on data related matters, including communication and change management along with training efforts. The Data Governance Manager will orchestrate the office and ensure there is organization-wide participation. The DGO is responsible for the oversight of the implementation of the Data Governance Framework and other related data management frameworks. All Data Governance program efforts are to be documented by the office.

The DGO exists within ADM(DIA). It is managed by the Data Governance Manager who reports to the Director of Data Policy and Digital Innovation (DPDI). DPDI is overseen by the CDO of DND/CAF who is the Director General of Data, Analytics, Strategy, and Innovation (DASI).

5.2.1.1 Role of the Data Governance Manager

The Data Governance Manager develops the policy instruments supporting the Data Governance Framework, and implements the following activities:

• Collaborate with all data stewards (executive, managerial and working level) as well as supporting roles in developing and implementing data governance within DND/CAF.
• Consult and collaborate on the launch of DAODs on Data Management and Analytics and instructional policy instruments on master data, reference data, and collaborate with ADM(IM).
• Develop, implement, and maintain a Data Issue and Risk Intake Form, Register, and Framework to provide guidance on risk mitigation and issue resolution.
• Determine data governance and management Key Performance Indicators (KPIs) and their thresholds, assist stewards with metric development to reflect progress on the KPIs
• Collaborate within DIA and with Data Officers on the establishment and implementation of all data management activities, such as:
  • Data Architecture
  • Data Integration and Interoperability
  • Data Modeling and Design
  • Data Quality
  • Data Security
  • Data Storage and Operations
  • Data Warehousing and Business Intelligence
  • Document and Content Management
  • Metadata Management
  • Reference and Master Data Management
• Ensure that guidance on access and use of enterprise (cross-government) data is communicated to all Data Officers and service owners to support the implementation of the Policy on Service and Digital^{Footnote 28}.
• Assist in consolidated reporting to the DDMB, the DG DPO Committee and other external committees on progress of implementing the DAODs on Data Management and Analytics.
• Work with the Policy team (of DPDI, in DASI) to define a formal process for periodic review and update of DAODs on Data Management and Analytics.
• Work with the Data Analytics and Enablement (DAE) team of DASI in their consultations with L1s on development of data lifecycle and business rules^{Footnote 29}.
• Work with the Data Literacy and Culture (DL&C) team of DASI to ensure data stewards of all levels, as well as Supporting Roles (especially Data Consumers) are provided with sufficient communications and training materials.

5.3 Within ADM(IM)

Information management specialists within ADM(IM) provide direction on records and document management services, archival services, open government services, forms management, and information architecture^{Footnote 30}. ADM(IM) and ADM(DIA) collaborates on the release of ‘open’ datasets to the Open Government Portal, and on the development of policy instruments on information/data architecture^{Footnote 31} and metadata management.

ADM(IM) also operates as a collaborative partner in supporting the infrastructure and tools that support data management activities that are executed in accordance with the Data Governance Framework. ADM(IM) is responsible for data security^{Footnote 32}, technology management, and implementation of data management tools. ADM(DIA) provides guidance on data management and access requirements to data held within ADM(IM) systems. ADM(DIA) and ADM(IM) have a shared responsibility for data quality, data interoperability, reinforcement of data culture, delivering a data literacy program, (see Joint Directive on Data Management [PDF, 16.4MB], paragraph 10 (accessible only on the National Defence network)), digital transformation, and implementation of artificial intelligence and machine-learning tools.

5.3.1.0 Role of the Information System Design Authority (ISDA)

The Information System Design Authority (ISDA) role will enable the Defence CIO in the delivery of timely, trusted, and secure information capabilities that contribute to the success of the Defence Team. ISDA participation in the Defence Information Programme governance will support the development and implementation of digital Defence policy instruments and architectures.

Enabling Defence Information Programme resources and capabilities in a decentralized service model requires a strong design authority capable of integrating the Defence Information Strategy across the DND and the CAF. By engaging internally and externally, the ISDA will facilitate improved planning and coordination of design, development, acquisition, and management of Defence information capabilities to ensure alignment of the Defence Information Strategy with Government of Canada (GC) digital standards and Treasury Board requirements for enterprise architectures.

The ISDA will ensure that Defence Information Programme resources and capabilities are consistent with Defence priorities and operations. Architectural designs and principles will be promulgated and used to assess proposed solutions and changes to existing solutions. Digital standards, best practices and reliable architectures will be shared so that they can be applied in a consistent manner throughout the life cycle of the digital resources and capabilities.^{Footnote 33}

6. Execution

6.2 Implementation Approach

6.2.1.0 Overview

To determine the right approach to support an L1’s implementation of the Data Governance Framework, it is crucial to first understand the L1’s current state of maturity. It is possible that an L1 is at different levels of maturity for different activities, however, it is important to not tackle too much in one area and let other activities fall by the wayside. An effective approach concurrently focuses its efforts across the vast activities defined in the Data Governance Framework. The table below (Figure 5: DGF Implementation Approach Guidelines) provides examples of the stages of maturity within the Data Governance Framework implementation activities. These examples can be used to help gauge current maturity and frame potential next steps for an L1. This enables the L1 to mature at a “crawl, walk, run” pace, while recognizing that some L1s may be ahead of others in their data governance and data management initiatives, and some may adopt the framework with more ease. This approach is adaptable to each L1, and the table is intended to provide examples and general guidelines to guide the way forward.

6.2.2.0 Step-by-Step

To begin the implementation of the Data Governance Framework, it is most effective to perform the following sequence of actions:

• Nominate a Data Officer for your L1 and communicate that nomination to the DGO within ADM(DIA).
• Ensure the Data Officer attends the DGWG.
• The Data Officer identifies their L1’s Data Domains and data assets.
• They nominate their Data Domain Steward(s) to represent their Data Domain(s).
• The Data Domain Steward(s) identifies their working-level stewards and formulates a Data Stewardship Working Group for their Data Domain within their L1.
• Use the Data Stewardship Working Group as a forum to identify, resolve and escalate data issues as required on a regular, ongoing basis.

Examples of the state of business throughout the implementation of the Data Governance Framework stages are demonstrated in the table below.

Figure 5: DGF Implementation Approach Guidelines

Crawl	Walk	Run
Key stakeholders are familiarized with the Data Governance Framework, there are plans for its future adoption.	The Data Governance Framework is being adopted, at a minimum, for critical data assets.	The Data Governance Framework has been adopted and is actively implemented through established business processes.
Data Governors, Data Officers – and, as required, Data Domain Stewards – have been identified.	In addition to executive level and managerial level stewards, working-level stewards are identified for critical data assets.	Each role of the Data Stewardship model at the executive or managerial level as well as working level are identified, and the model is applied across the L1.
There is a method determined and initiatives underway to identify all critical data assets.	All critical data assets are identified and governed.	All critical data – and possibly additional data assets – is (are) identified, governed, and monitored on a regular, ongoing basis.
There are engagements with ADM(DIA) to identify a suitable representative for the Data Governance Working Group.	There is, at a minimum, an interim representative that regularly attends the Data Governance Working Group.	There is sufficient presence from the L1 and regular, active participation in the Data Governance Working Group.
The concept of the Data Stewardship Working Group(s) is understood, and the Data Officer or Data Domain Steward are planning to establish it (them).	There is some form of Data Stewardship Working Group though attendance of all the stewardship groups or frequency may be inconsistent.	There is (are) sufficient Data Stewardship Working Group(s) and participation in it (them) for the domain that meet on a regular basis.
Data issues and risks are being identified but there are no resolution or escalation processes.	Data issues and risks at the working level are addressed as required, at a minimum, for critical data assets.	Data issues and risks that remain unresolved at the working level are escalated to ADM(DIA) and the Data Governance Working Group.
Data governance and data management metrics are being developed, there is awareness of ADM(DIA) KPIs and thresholds.	Data governance and data management metrics are established and monitored for, at a minimum, critical data assets. There is knowledge and understanding of ADM(DIA) KPIs and thresholds.	Data governance and data management metrics are established and monitored regularly against KPIs and thresholds.

6.3 Working Groups

6.3.1.0 Overview

Working groups facilitate the resolution of data issues through problem-solving discussions and activities. They also provide a means to escalate data issues as required. There are two levels of working groups, the Data Governance Working Group (DGWG) which provides a forum for the Data Officers and Data Advisors, and the Data Stewardship Working Groups (DSWGs) which provides a forum for the Data Domain Stewards, their working-level stewards, and other supporting roles as required.

6.3.2.0 Data Governance Working Group (DGWG)

The role of the DGWG is described in the Terms of Reference.^{Footnote 34} The working group has been developed to fulfill the following activities:

The DGWG has been established by the DG DPO Committee to facilitate the implementation of the Data Governance Framework as well as to identify and resolve data governance, data management and data access issues. The DGWG’s Terms of reference, in turn, should be read and understood in conjunction with the Data Governance Framework. Members of the Working Group are typically Director-level or Military equivalents who have been identified as their L1 Data Officer. The group will also promote data quality, security, usability, accessibility, and other best practices.^{Footnote 35}

Issues that remain unresolved at the DGWG which may be candidates for escalation will first be reviewed by the Chief Data Officer. Following revision, a solution may be proposed, or the decision made to escalate the issue to the DG DPO Committee and/or the DDMB.

6.3.3.0 Data Stewardship Working Groups (DSWGs)

Each Data Domain Steward must create their own Data Stewardship Working Group. These working groups meet monthly, at a minimum. These working groups are a gathering of Data Stewards and, Data Custodians within the same Data Domain, but invitations can be extended to any supporting role as required to facilitate discussion, seek consultations, or resolve issues. There is no strict format to these working groups, each Data Domain Steward can design them as required. The working groups identify, resolve, and escalate data issues and risks, collaborate to design metrics which support ADM(DIA) data governance and data management KPIs and thresholds, as well as standardize processes and definitions within their domain to coincide with DND/CAF processes and definitions. Further, these working groups are responsible for identifying or appointing the working-level stewards, provide training materials to them and promote existing rules and policies.

6.4 Data Stewardship Model

6.4.1.0 Overview

The Data Stewardship Model supports the execution of data governance and data management activities. Stewardship exists in multiple tiers from executive-level to working-level stewards. Executive-level or managerial-level stewards include Data Governors, Data Officers and Data Domain Stewards. Working-level stewards include Data Stewards, and Data Custodians. Where possible, the roles within the Data Stewardship model will be assigned to existing roles within DND/CAF to ease adaptability of the Data Governance Framework. This will minimize the need for net new resources, where existing resources can be leveraged, or their responsibilities recalibrated. Each L1 must designate these roles within their L1 to facilitate the implementation of the Data Governance Framework as it is the foundation to the implementation of all other data and data management policies, standards, best practices, and processes. The diagram below (Figure 6) demonstrates the hierarchy of these stewardship roles.

Figure 6: Stewardship Model & Personas

6.4.2.0 The Chief Data Officer (CDO)

The Chief Data Officer is the authority who ensures the resolution of data issues, oversees decisions on data management that have a horizontal impact across L1s, and uses their discretion to escalate issues as required to executive-level decision-making bodies. The Chief Data Officer oversees and encourages collaboration among Data Officers to ensure that each L1s’ interests in data decisions are heard and respected. The Chief Data Officer role is within ADM(DIA), they are the Director General of Data, Analytics, Strategy, and Innovation (DASI).

6.4.3.0 Role of the Data Governors

The DDMB and DG DPO L1 representatives are de facto Data Governors, they are accountable and responsible for the initiation of the implementation of the Data Governance Framework and its data stewardship model. Data Governors serve as champions and advocates for data management and analytics. They collect input on the role of data to support key L1 initiatives and gain understanding of and support for data and analytics activities. They are responsible for communicating the data and analytics DAODs to their organizations, provide feedback and data to guide policy and best practices over time; and provide explicit direction to Data Officers and Data Advisors on stewarding the data within their control.

6.4.3.1 Scope of the Data Governors

The DDMB Data Governor is ultimately accountable for ensuring the designation of a Data Officer for each L1, and Data Advisor for each Data Domain. The DG DPO Data Governor for each L1 is responsible for the identification of the Data Officer for their L1. The DG DPO is also responsible for deciding which L1 or organizational business unit will be responsible for which Data Domain and ensuring a Data Advisor is identified for those Data Domains. ADM(DIA) supports the Data Governors in pursuing these responsibilities.

6.4.3.2 Responsibilities of the Data Governors

The Data Governor’s responsibilities are as follows:

• Identifies their L1 Data Officer representative for DGWG.
• Identifies a Data Advisor where their L1 is given functional authority of a Data Domain.
• Provides executive leadership and engagement needed to ensure departmental programs to become data driven.
• Responsible for strategic decision-making and alignment.
• Addresses departmental issues on data sharing for interoperability with allies and FVEY community.
• Addresses departmental issues on the management of data assets, including data held within third party owned and operated applications.
• Endorses data and analytics priorities and investments.
• Collaborates with other L1 representatives to identify data and analytics assets in scope.

6.4.3.3 Data Governor’s Relationships with Other Data Roles

The key relationships of Data Governors include:

• ADM(DIA) – provides direction on policy creation considering the DND/CAF Data Strategy and objectives, communicates overall programme status based on aggregation of Data Officer input to Deputy Minister and Chief of Defence Staff, and is Chair and a voting member on the DDMB.
• Vice Chief of Defence Staff – provides lead on CAF approach interests and priorities and is a voting member on the DDMB.
• Chief Financial Officer – provides direction on financial investment data and is a voting member on the DDMB.
• Chief Information Officer (ADM[IM]) – enables cross-domain integration and interoperability, provides input regarding opportunities for digital enablement, and is a voting member on the DDMB.
• Other L1s – Data Governors serve as champions and advocates for data management and analytics. They collect input on the role of data to support key L1 initiatives and gain understanding of and support for data and analytics activities. They are responsible for communicating the data and analytics DAODs to their organizations, provide feedback and data to guide policy and best practices over time; and provide explicit direction to Data Officers and Data Domain Stewards on stewarding the data within their control.

6.4.4.0 Role of the Data Officer

The Data Officer is a director-level representative who is ultimately accountable for their L1’s data management activities, and for promoting the horizontal alignment across DND/CAF L1s. They are responsible for attending the DGWG to provide their support in resolving data issues across DND/CAF. The Data Officer is a champion for data within their L1, they play a key role in enabling access and ethically leveraging these data assets for achieving DND/CAF goals. The Data Officer acts as the primary point of responsibility, accountability, and activity for the assessment, improvement, ongoing fitness for purpose, and overall conformance of that data. Data Officers appoint Data Domain Stewards as required to facilitate stewardship of the Data Domains within their L1 to facilitate their data governance and data management activities.

For a current list of Data Officers, please see the DGWG members under ADM (DIA) SharePoint site^{Footnote 36} (accessible only on the National Defence network).

6.4.4.1 Scope of Data Officer Role

The Data Officer is responsible for the oversight, monitoring, and implementation of data standards and guidelines on the management of the L1. The vehicle by which they do so is by appointing Data Domain Stewards for each of the Data Domains within their L1. If issues are across multiple L1s they should initially be addressed by Data Officers at the DGWG. The Chief Data Officer will support as required. If necessary, the issue may be escalated to the DG DPO Committee and escalated further, if necessary, to the DDMB.

6.4.4.2 Responsibilities of the Data Officer

In collaboration with ADM(DIA), the main purpose of the Data Officer is to improve, protect, and collaborate with other L1s and Data Advisors on the data. In so doing, the Data Officers is responsible for assessing the current state of data access and data management activities, as well as ensuring that security, privacy and retention and disposition activities are conducted within their L1.

The responsibilities are as follows:

• Identifying the Data Domains, their assets, and sources within the L1.
• Appointing Data Domain Stewards to sufficiently represent each Data Domain within their L1.
• Ensuring horizontal alignment in Data Domains that span multiple L1s.
• Consulting with Data Advisors and SMEs to ensure their Data Domain Stewards have sufficient guidance and awareness of processes, standards, and best practices within their Data Domains.
• Negotiating with other L1s on the roles and responsibilities for the management and use of data. These roles and responsibilities should take the form of a Responsible, Accountable, Consulted, Informed (RACI) chart for each phase of the data lifecycle^{Footnote 37}.
• Working within their L1 and with other Data Officers to implement change, in support of ADM(DIA)’s guidance and DAODs on master data, reference data, and metadata.
• Documenting and communicating business rules specific to their L1. Examples of these business rules are data validation, derivation, referential integrity, and discovery.
• In collaboration with ADM(DIA), is responsible of for documenting the security classification requirements of data within its systems (in collaboration with ADM[IM]) and identifying how the business rules specific to the domain are developed, implemented, audited, and monitored.
• Ensuring that documentation on business rules is collected, recorded, and communicated to other L1s.
• Monitoring and tracking ongoing data fidelity (e.g., quality and consistency) levels, mitigate any risks or issues, and protect the data from deliberate or accidental harm^{Footnote 38}.
• Correcting data quality flaws that cannot be fully addressed by automated means.
• Reporting regularly to the DGWG on the implementation of the Data Governance Framework.
• Providing input to the DGWG for improvements in the work of data governance and stewardship.
• Interpreting, promoting, and implementing activities to ensure target goals for data fidelity improvement and adherence with other data related DAODs, policies, and frameworks within the ADM(DIA) policy suite^{Footnote 39}.
• In collaboration with ADM(DIA) and ADM(IM), identifying optimal approaches for resolving data quality or consistency issues to achieve agreed targets identified within the ADM(DIA) Data Quality Framework^{Footnote 40}.

6.4.4.3 Data Officer’s Relationships with Other Data Roles

The Data Officer’s role is collaborative and interacts with Data Officers from other L1s and with supporting roles as required.

Specifically, the Data Officer works closely with:

• ADM(DIA) – collaborating on approaches to stewardship activities and facilitates data quality and consistency across DND/CAF.
• Data Governance Working Group – receiving guidance and responds to queries from working group members, reports on progress as well as identifies and resolves issues.
• Peer Data Officers – collaborating on stewardship activities at L1 touchpoints, where Data Officers have overlapping or adjacent scope.
• Working-level stewards – to collaborating and supporting working-level stewardship on the practical implementation of data management activities.
• Data Domain Stewards – the Data Officers ensure their Data Domain Steward(s) establish their Data Stewardship Working Group(s).
• Data Advisors – they are consulting with Data Advisors as required to gather information on processes, standards, and best practices for their Data Domain Stewards. Where a Data Domain exists in multiple L1s; they work with other Data Advisors to propose and recommend process improvements on domain stewardship.
• Analytics Support Centre Managers – collaborating on the aggregation and integration of data to support the use of analytics^{Footnote 41}.
• Other Supporting Roles – consult with other Supporting Roles as required.

6.4.5.0 Role of the Data Domain Steward

The Data Domain Steward is the subject matter expert of a Data Domain within their L1, they are knowledgeable of their Data Domain’s policies, standards, best practices, and processes. They are responsible for propagating this knowledge within their L1 to working-level stewards (and to other Supporting Roles as required) and overseeing the implementation. They ensure the assessment, improvement, ongoing fitness for purpose, and overall conformance of that data with their Data Domain, within their L1. They formulate a Data Stewardship Working Group within their L1 to facilitate working-level discussions on data-related matters within their Data Domain with their L1. If a data issue cannot be resolved within their Data Stewardship Working Group, the Data Domain Steward escalates the issue to their L1 Data Officer for resolution. If the issue exists within a Data Domain that spans across multiple L1s and cannot be resolved amongst Data Domain Stewards, the data issue is escalated to the Data Officer who then facilitates horizontal discussions.

6.4.5.1 Scope of Data Domain Steward

The Data Domain Steward is responsible for the propagation and overseeing the implementation of their Data Domain’s policies, standards, best practices, and processes within their L1. They are responsible for the oversight of data, monitoring the management of data entities within that Data Domain within their L1, and enforcement of data processes, standards, and best practices. When deviations from the DAODs and data guidelines and standards are detected and not resolved through regular resolution processes, the Data Domain Steward is responsible for the escalation to their Data Officer.

6.4.5.2 Responsibilities of Data Domain Steward

The responsibilities are as follows:

• Identifying their working-level stewards, creating, and facilitating a Data Stewardship Working Group for their Data Domain within their L1.
• Promoting the propagation of their Data Domain’s policies, standards, best practices, and processes via their working-level stewards (and other Supporting Roles as required) and as prescribed by their Data Advisor and ADM(DIA).
• Monitoring and overseeing data within the Data Domain and resolving issues in data quality, usage, and protection via their Data Stewardship Working Groups.
• Escalating unresolved issues to their Data Officer.
• Retaining and overseeing the maintenance of the data assets for the Data Domain within their L1.
• Documenting and communicating business rules for the Data Domain within their L1. The Data Domain Steward, in collaboration with the Data Officer, has the responsibility of documenting the security classification of data, and how the business rules around the Data Domains are audited and monitored.
• Ensuring that the documentation is collected, recorded, and communicated to their working-level stewards (and other Supporting Roles as required) and their Data Officers.
• Monitoring any discrepancies and taking action to mitigate any discrepancies, in coordination with working-level stewards (and other Supporting Roles as required).
• Updating records, following direction from the Data Officer and Data Advisors.
• Ensuring that personal information is managed across the Data Domain in accordance with the requirements of the Privacy Act. (Personal information may only be collected with legitimate authority and can only be used or disclosed in accordance with the applicable Personal Information Bank; or in accordance with a permissible disclosure described in section 8(2) of the Privacy Act; or with the expressed consent of the individual.)

6.4.5.3 Data Domain Steward’s Relationships with Other Data Roles

The Data Domain Steward’s role is very collaborative and interacts with working-level stewards, and supporting roles within the Data Domain, within their L1. They report on data-related matters to their Data Officer.

Specifically, the Data Domain Steward works closely with:

• Data Officer – collaborates on approaches to stewardship activities, improves data quality, and facilitates data consistency across Data Domain, report on unresolved data issues for escalation.
• Data Advisor – subject matter experts in their Data Domain’s policies, standards, best practices, and processes, they are well-versed in the Data Advisor’s mandates for their Data Domains. Direct communication and engagements with Data Advisors are led by the Data Officer.
• Data Stewardship Workings Groups – creates a Data Stewardship Working Group for their Data Domain within their L1. They identify their working-level stewards for participation in the working group and extend invitations to supporting roles as required.
• Peer Data Domain Stewards – collaborates with Data Domain Stewards within their L1 as required and where there may be dependencies between Data Domains. Where a Data Domain exists in multiple L1s, Data Domain Steward’s report to their Data Officer to propose and recommend possible resolutions. These unresolved issues are discussed among Data Officers at the DGWG.
• Working-level stewards – collaborates and supports working-level stewardship on the practical implementation of data management activities via their Data Stewardship Working Group and on an as-needed basis.
• Data Consumers – negotiates and resolves issues on the use and reuse of data to support the business of defence.
• Other Supporting Roles – consults with other Supporting Roles as required.

6.4.6.0 Role of the Data Steward

Data Stewards are working-level stewards; typically, this title is designated by a Data Domain Steward to an existing incumbent who is actively managing data on a regular basis. They are directly responsible for analyzing and maintaining data quality, access and other data management outcomes and activities. Data Stewards ensure there is alignment with business operations and the management of the data lifecycle as well as monitor and act on data quality issues and risks.

6.4.6.1 Scope of the Data Steward

Data Stewards are responsible for the implementation of data governance and data management activities within their operational responsibilities. The Data Steward reports on data issues and activities to their Data Domain Steward and collaborates with other working-level stewards and other Supporting Roles.

6.4.6.2 Responsibilities of the Data Steward

The responsibilities are as follows; this list is not exhaustive and can be adapted as required for each Data Domain:

• Analyze, monitor, and report on data quality.
• Develop data metrics to support ADM(DIA) data governance and data management KPIs.
• Track metrics to ensure compliance with ADM(DIA) KPI thresholds.
• Ensure the quality and fitness for purpose of the data.
• Identify and resolve data issues (either identified by pro-active monitoring, or re-active as identified by other stakeholders) and escalate to their Data Domain Steward and/or Data Stewardship Working Group as required.
• Implement and enforce data standards, policies and definitions defined by ADM(DIA) or Data Advisors.
• Recommend possible changes to data policies, standards, rules, and processes based on operational findings to their Data Domain Steward.
• Maintain data, and metadata according to policies, standards, rules set by ADM(DIA), the Data Advisors and the strategic direction of the DGO.

6.4.6.3 Data Steward’s Relationship with Other Data Roles

• Data Domain Steward – Data Stewards report on data issues and activities to their Data Domain Steward.
• Data Stewardship Working Group – they participate in the Data Stewardship Working Group(s) for their Data Domain(s).
• Other Supporting Roles – Data Stewards consult with other Supporting Roles as required to ensure their processes are being delivered in the best interest of data usability, accessibility, and security.
• Data Custodians – Data Stewards collaborate with Data Custodians to describe their business needs to determine technological solutions as required.
• Data Consumers – collaborate with Data Consumers to ensure data is usable and fit-for-purpose.

6.4.7.0 Role of the Data Custodian

Data Custodians technical working-level stewards; typically, this role or title is designated to an existing incumbent who is actively managing technology solutions. Data Custodians are the technical support of data stewardship activities and have detailed knowledge on how applications, data stores, and Extract, Transform and Load or Extract, Load, and Transform processes. Data Custodian activities includes data integration, database administration, and data quality specialists. Under the data governance approach, they identify opportunities to enable data sharing through data integration and interoperability across the department.

Within ADM(IM)’s DIMSecur, subject matter expertise on security is founded on the need to ensure that sensitive information under the department’s control is protected according to the Policy on Government Security and any relevant legislation, policy or agreement. Information security functional specialists are responsible for ensuring protection of confidentiality, integrity, and availability of data and information. In respect of the Data Governance Framework, ADM(DIA) will collaborate with ADM(IM)’s DIMSecur on developing data-centric risk and data-centric security approaches across the department.

6.4.7.1 Scope of the Data Custodian

Data Custodians provide technical support and collaborate with working-level stewards to implement technical solutions and perform technical activities required to facilitate data governance and data management activities. They can be identified by ADM(IM), or they are other technical resources who can provide these services.

6.4.7.2 Responsibilities of the Data Custodian

The responsibilities are as follows (this list is not exhaustive and can be adapted as required for each Data Domain):

• Implements and maintains consistency in how data is processed, stored, transported, and provided to users.
• Understands and reports security risks and how they impact the confidentiality, integrity, and availability of information assets.
• Ensures access to the data is authorized and controlled.
• Implements appropriate physical and technical safeguards to protect the privacy (i.e., confidentiality), integrity and availability of information assets associated with the data and assess the effectiveness of these safeguards.
• Ensure data added to data sets align with the business data model.
• Ensure versions of Reference and Master Data are maintained with historical changes.
• Ensure change management practices are applied in maintaining the database.
• Ensure data content and changes can be audited.
• Enforce technical standards for data within their care.

6.4.7.3 Data Custodian’s Relationship with Other Data Roles

• Data Stewards – Data Custodians implement the technical components to support the business requirements expressed by the Data Stewards.
• Data Stewardship Working Group – Data Custodians attend the Data Stewardship Working Group(s) to assist and provide clarity and consultations on technical matters to the Data Domain Steward(s) and Data Stewards (as well as other Supporting Roles as required).
• Other Supporting Roles – collaborate with DND/CAF Information Security Functional Specialists who are responsible for ensuring protection of the confidentiality, integrity, and availability of information in their area of responsibility as per NDSOD Chapter 6 – Security of Information, and Treasury Board Secretariat’s Policy on Government Security^{Footnote 42} and its supporting policy tools. As well as with DND/CAF Information Management Officers who are information management functional specialists at the group or organizational level.

6.5 Supporting Roles

6.5.1.0 Overview

Supporting Roles of the Data Stewardship Model facilitate the effective execution of data governance and data management activities. The involvement of these roles will provide varying lenses which promote more dynamic development of data governance and data management practices within DND/CAF. Data Officers and Data Domain Stewards should provide sufficient opportunity for the necessary Supporting Roles to collaborate. The Supporting Roles ensure the practices are fit-for-purpose and can be practically applied across all L1s. The Data Governance Framework does not prescribe responsibilities of Supporting Roles but acknowledges the impact they have on the responsibilities and capabilities of each role in its Data Stewardship Model.

6.5.2.0 Analytics Support Centre, Managers’ Coordination Committee (ASC MCC)

Analytics Support Centre – Managers Coordination Committee (ASC – MCC) is the working level data governance body convened by the Director of Policy and Digital Innovation, ADM (DIA) to support its functional authorities in analytics. The ASC – MCC is a working-level forum to provide advice on analytics and escalates issues requiring shaping or approval to higher level governance bodies.

The MCC is a managers-level committee and aligns with and supports the existing data governance committees. Members are expected to work with their identified L1 Data Officers from the DGWG on issues concerning data management, governance, and access. Issues and items can then be escalated up to the DG DPO and DDMB as required.^{Footnote 43}

6.5.3.0 Data Citizen

In DND/CAF, everyone is considered a Data Citizen. It is important to recognize that not everyone will be in contact with data or actively managing data on a day-to-day basis. However, everyone has the responsibility in those scenarios as they arise to respect data management best practices, use the data appropriately, and to abide by relevant privacy and security requirements. They have the responsibility of diligence in data-related matters. There must be sufficient communication and awareness within DND/CAF to express this inherent responsibility and to promote an effective data culture.

6.5.4.0 Data Advisor

Data Advisors are the DND/CAF authority of a Data Domain and are regularly consulted by L1s to ensure data activities adhere to the Data Domain’s relevant policies, standards, best practices, and processes. They ensure alignment with the critical priorities and goals of their Data Domain to support DND/CAF business of defence. They have authority to create policies and standards for their Data Domain. They must ensure their policies, standards, best practices, and processes for their Data Domains are sufficiently communicated to the Data Officers to ensure that the Data Officers can adequately equip their Data Domain Stewards with the required knowledge. The ADM(DIA) and the Data Advisors consult on data policy and standards creation to ensure consistency across the DND/CAF. There is one Data Advisor per Data Domain. The Data Advisors must have representation at the DGWG.

6.5.5.0 Data Consumer

Data Consumers express their business needs which identify desired outcomes and targets. This provides a benchmark to signify how data governance and data management activities should be designed to ensure that they are fit-for-purpose to support those needs. Data Consumers play an important role in maintaining the data’s integrity while using and re-using data created, collected, and managed within DND/CAF. These are the users of the data, and ultimately, this group’s needs must be fulfilled to facilitate business activities. Data Consumer input should be considered in all decisions involving data.

The role of the Data Consumer is supported by enabling access, use and re-use of data within the Data Domains to support the business of defence. The associated Data Manager(s) is (are) responsible for ensuring that data is consumed according to any specific security classification and privacy requirements identified by ADM(DIA) and the Data Advisors. Considerations such as these are critical when transplanting or transferring data from one environment to another.

Data Consumers exist at multiple HR classification levels. The level of data literacy required to assess and analyze data to support the business of defence differs across these HR classification levels. ADM(DIA) training team will work with Data Consumers on supporting data literacy and culture through DND/CAF.

6.5.6.0 Data Producer

While Data Consumers use the data, Data Producers are those who create it. Data Producers are the ultimate source of data. The data can be sourced from across the DND/CAF, from external partners, other government departments, third parties, and so on. This means that Data Producers are not solely within the DND/CAF. However, within the DND/CAF, Data Producers are often simultaneously taking on other roles, perhaps as working-level stewards, or other Supporting Roles. The role they play as producers of the data is critical to the management of data as they are the creators.

6.5.7.0 Business Data Specialist

Business Data Specialists ensure that data governance and data management activities are fit-for-purpose. They play a key role in reviewing the data to ensure that it meets defined criteria before the data is released and can be consumed and used for ensuing activities. They are subject matter experts (SMEs) within the business units who – unlike Data Stewards – are not actively engaging in data management activities with the data. Rather, the Business Data Specialists are individuals who are SMEs of the business within the L1 or Data Domain.

The Business Data Specialist is responsible for identifying deviations from the DAODs and subject-specific guidelines and standards and resolving them through automated or manual practices and tools.^{Footnote 44} Business Data Specialists actively engage with working-level stewards and attend the DGWG or DGSWs as required.

6.5.8.0 Data Professional

Data Professionals are onboarded to provide expertise in particular areas or activities of data management or information technology. They are hired specifically to a role or position as a professional to provide a service, whether they are a full-time employee or consultant. There are varying types of Data Professionals who hold many different titles such as Data Scientists, Data Engineers, Data Architects, Data Analysts, and many others. The role they play, their scope of work and their responsibilities are defined within their statements of work and are unique to each initiative they support. The Data Professionals are expected, as required, to attend the DGWG and DSWGs, and to support and consult with data stewards of all levels.

Appendix A: References

Functional Authority documentation:

• Accountabilities, Responsibilities, Authorities (ARA) Framework for ADM(DIA) [PDF, 300KB] (accessible only on the National Defence network)
• CDS/DM Joint Directive on Data Management [PDF, 1.6MB] (accessible only on the National Defence network)
• CDS/DM Joint Directive to Develop and Operationalize a Defence Program Analytics Capability [PDF, 3.7MB] (accessible only on the National Defence network)

Internal Policy Instruments:

• DAOD 1000-0, Foundation Framework for Defence Administrative Orders and Directives
• DAOD 1000-6, Policy Framework for Information and Information Technology Management
• DAOD 1000-8, Policy Framework for Safety and Security Management
• DAOD 1001-0, Access to Information
• DAOD 1002-0, Administration of the Privacy Act
• DAOD 2011-0, Enterprise Architecture
• DAOD 3000-0, Materiel Acquisition and Support
• DAOD 3008-0, Intellectual Property
• DAOD 6000-0, Information Management and Information Technology
• DAOD 6001-0, Information Management
• DAOD 6001-1, Information Management Programme
• DAOD 6003-0, Information Technology Security
• DAOD 6500-0, Data Management and Analytics
• DAOD 7023-0, Defence Ethics
• DAOD 8008-0, Defence Intelligence

DND and ADM(DIA) documentation:

• Strong, Secure, Engaged: Canada’s Defence Policy
• The Department of National Defence and Canadian Armed Forces Data Strategy
• Data Quality Framework (accessible only on the National Defence network)
• Analytics in DND/CAF: Vision and Guiding Principles
• ADM (DIA) SharePoint site (accessible only on the National Defence network)
• Data Governance Working Group Terms of Reference (DGWG ToR) (accessible only on the National Defence network)

Treasury Board of Canada Secretariat Policy Instruments:

• Policy on Access to Information
• Policy on Privacy Protection
• Policy on Service and Digital
• Directive on Service and Digital
• Guideline on Service and Digital
• Directive on Automated Decision-Making

Legislation and other sources:

• Privacy Act
• Access to Information Act
• Data Management Body of Knowledge (DMBoK) – Data Management Association (DAMA-I) [PDF, 10.1MB] (accessible only on the National Defence network)
• DAMA Dictionary of Data Management – Data Management Association (DAMA-I) [PDF, 4.3MB] (accessible only on the National Defence network)
• First Nations OCAP Principles [PDF, 115KB] – Association of First Nations

Appendix B: Definitions

analytics (analytique)

Systematic computational transformation of data into insights, for the purpose of making better decisions. (Defence Terminology Bank record number 696416)

artificial intelligence (intelligence artificielle)

Information technology that performs tasks that would ordinarily require biological brainpower to accomplish, such as making sense of spoken language, learning behaviours, or solving problems. (Directive on Automated Decision-Making, Treasury Board)

big data (mégadonnées)

Data produced in high volume, at high speed and in various formats, and which is too complex to be handled with traditional data-processing software. (Defence Terminology Bank record number 695863)

business intelligence (intelligence d'affaires)

The applications, infrastructure, tools and best practices that enable access to, and analysis of, information to improve and optimize decisions and performance. (Defence Terminology Bank record number 695860)

data (données)

Set of values of subjects with respect to qualitative or quantitative variables representing facts, statistics, or items of information in a formalized manner suitable for communication, reinterpretation, or processing. (Policy on Service and Digital, Treasury Board)

Note – In the DND and the CAF, data is created, collected and used both in military operations and exercises, and in corporate administrative processes.

data architecture (architecture des données)

An integrated collection of master design documents at different levels of abstraction that govern how data is collected, stored, arranged, used and removed.

Note – Data architecture is classified by descriptions of all the containers and paths that data takes through an organization's systems. (Defence Terminology Bank record number 695861)

data asset (ressource des données)

An entity comprised of data from any source that can be governed and managed and that has potential to provide value or produce benefit. This can include data sets, databases, big data, and system and application output files. (Defence Terminology Bank record number 696417)

data governance (gouvernance des données)

A system of decision rights and accountabilities applicable to data-related processes.

Note – This system describes which action can be taken on which data asset, by whom, under which circumstances and using which methods. (Defence Terminology Bank record number 695865)

data integration (intégration des données)

The movement and consolidation of data within and between data stores, applications and organizations, into consistent forms either physical or virtual. (Defence Terminology Bank record number 695866)

data management (gestion des données)

The development, execution and supervision of plans, policies, programs and practices that deliver, control, protect and enhance the value of data and information assets throughout their life cycles. (Defence Terminology Bank record number 27521)

data quality (qualité des données)

A degree or level of confidence that the data provided meets requirements of the data user in terms of characteristics such as accuracy, completeness and reliability. (Defence Terminology Bank record number 33436)

digital (numérique)

Processes, practices and technologies related to the production, storage, processing, dissemination and exchange of electronic information and data. It refers to, among other things, information and communications technologies, infrastructures, and the information and data they produce and collect. (Policy on Service and Digital, Treasury Board)

domain (domaine)

A specific field of knowledge or expertise. (Defence Terminology Bank record number 21857)

enterprise data model (modèle de données d’entreprise)

A holistic, enterprise-level, implementation-independent conceptual or logical data model that provides a common and consistent view of data across the enterprise. (Defence Terminology Bank Record number 696418)

information (information)

The representation that a human or a machine assigns to data, facts or knowledge by means of known conventions such as reports, events, processes, decisions, ideas or opinions in any medium or form. (Defence Terminology Bank record number 696374)

information asset (ressource d’information)

A body of information defined and managed as a single unit so the body of information can be understood, shared, protected and exploited effectively.

Note – An information asset has recognizable and manageable value, risk and content for DND business and CAF operations. (Defence Terminology Bank record number 696375)

interoperability (interopérabilité)

The ability of different types of electronic devices, networks, operating systems, and applications to work together effectively, without prior communication, to exchange information in a useful and meaningful manner. (Policy on Service and Digital, Treasury Board)

master data (données maîtres)

Data that provides the context for business activity data in the form of common and abstract concepts that relate to the activity.

Note – Master data includes the details (definitions and identifiers) of internal and external objects involved in business transactions such as customers, products, employees and vendors. (Defence Terminology Bank record number 695867)

metadata (métadonnées)

Data that describes data itself, the concepts the data represents and the connections between the data and concepts. (Defence Terminology Bank record number 695869)

predictive analytics (analyse prédictive)

The use of regression analysis, forecasting, multivariate statistics, pattern matching, predictive modeling or other techniques to provide insight as to what could happen in the future. (Defence Terminology Bank record number 696419)

reference data (données de référence)

Data that defines a set of permissible values that are used by other data fields and do not generally change, for example, units of measurement and country codes. (Defence Terminology Bank Record number 696420)

Appendix C: L1 Data Considerations

Corporate Secretariat (Corp Sec)

Within the Corp Sec, the Directorate Access to Information and Privacy (DAIP) is responsible for the administration of both the Access to Information Act and the Privacy Act, which allow individuals right of access to information that is contained in government records. DAIP is also responsible for providing guidance and direction relating to the management of personal information to ensure compliance by the DND and the CAF with the administration of the Privacy Act.

ADM(Policy)

ADM(Pol) provides support on policy development related to data, including data sharing, ethics, and the use of future data-driven capabilities. ADM(DIA) will need to coordinate with ADM(Pol) to create coherent data policies for DND/CAF.

Judge Advocate General (JAG)/Canadian Forces Legal Advisor (CFLA)

The Office of the JAG and the DND/CF LA support the Data Governance Framework when providing legal advice when requested by a data steward, in relation to any law or legal obligations governing the collection, use, disclosure, retention, disposition, or storage of that data. Legal experts within JAG/CFLA ensure that the department meets regulatory, statutory, and compliance requirements, and is the lead respondent involved in litigation, investigation, or legal action.

In particular, DND/CFLA has primary responsibility for advising on legal aspects of the application of the Access to Information Act and the Privacy Act, as well as for supporting DND/CAF in meeting its obligation to produce information in relation to legal proceedings.

ADM(Defence Research and Development Canada)

ADM(DRDC) holds the functional authority for Scientific Integrity Policy and advises Data Governors of the DDMB representatives on data-centered innovations.

ADM(Review Services) – Regulation and Compliance

Across DND, subject matter experts play a key role in identifying, assessing, and mitigating data-centered risk within the department. The target state is that data have a reasonable and suitable guarantee of authenticity and reliability. In particular, that threats are identified, and the data has protection from loss, corruption, and the threat of privacy or security breaches.

Appendix D: Out of Scope

During the Data Governance Framework consultations, many valid concerns and comments were raised which foreshadowed the requirements for additional documents and resources from ADM(DIA). These resources will be made available, but are not within the scope of the Data Governance Framework itself:

• Issues & Risks Management Framework
• Metrics and KPIs
• DASI Role Distinctions
• Data Governance Framework Communications Strategy
• Data Stewardship Register
• Data Management Frameworks (including the Data Quality Framework)
• DG DPO & DDMB ToR content
• Data Governance Tools
• Stewardship Responsibilities specific to each L1 (DGF provides generalized responsibilities)
• Alignment with/mapping of external stewardship models

Appendix E: Contributors

Special thanks are shared with the following organizations who contributed to the content and revision of the Data Governance Framework.

Appendix F: Citations