1. Statistical Metadata Strategy and GSIM Implementation in Canada Statistics Canada

2. Background: Corporate Business Architecture (CBA )  Five of the architectural principles of the CBA review of particular significance to statistical metadata are: metadata-driven processes; maximizing reuse of existing corporate systems; optimise use of corporate services; enforcing reuse of concepts and classifications and governance of data and metadata architectures. 2

3. Background: Metadata Architecture Modernization (MAM)  Strategy for Statistical Metadata Management was approved in 2013  Strategy is being implemented through a CBA project: the MAM project approved in 2014  goal is to improve interoperability between our systems and improve the management of metadata 3

4. Processes use metadata Standardized metadata in all processes Metadata is managed Enterprise- focused governance Single point of access to metadata Standard formats meet user needs Users have the metadata they need Information architecture supports use GOALS from the strategy Initiate IMDB re-design project Develop high-level architecture Develop centres of responsibility Fill metadata gaps Initiate single point of access Adopt structure and content standards Communication and training ACTIVITIES of the MAM project Project activities based on the Strategy Fill policy gaps Elaborate Architecture for IMDB (high level) Develop operational governance 4

5. Supports information architecture governance Standardized metadata for collaborative design and execution Links to dissemination standards (e.g. DDI, SDMX) Accelerates standardized interfaces between services (e.g. Collection) StatCan’s “Plug and Play” architecture – EAIP & components Registry support - standardized metadata, data framework Strategy, governance, policy revision MAM is part of corporate approach to transformation 5

6. Move towards common components and capabilities 6

7. GSIM 1.1 at Statistics Canada  Information architects and project teams working on the design of new systems or the development of services for existing systems: adopted to specify, design, and implement components for integration into “plug’n’play” architectures and link to standard formats (e.g. DDI, SDMX). GSIM Objects will be the inputs/outputs of GSBPM statistical sub-processes implemented as services within StatsCan’s CBA Service Approach.  Standards Division for structuring metadata, as a common vocabulary (concepts group and statistical classification model) 7

8. Classification Exchange Model 8

9. Other Common Models 9

10. Work supporting the architectural transformation  Creation of a governance committee to manage information architecture  Review and updates of policy instruments  Training and communication 10

11. The Information Architecture Governance Committee  A high-level governance committee is being developed to ensure a corporate approach to statistical metadata management. This committee is expected to: Coordinate the operational governance of the Agency’s information architecture Coordinate the adherence to principles and standards for statistical information and metadata management Assist and advise on the development and application of the corporate information architecture Assist and advise on the review of policies and procedures. Identify challenges, issues and opportunities in the development and implementation and coordinate these in a timely manner 11

12. Statistical Metadata Policy Proposal Directive on Statistical Standards and Frameworks Directive on Informing Users of Data Quality and Methodology Policy on Statistical Metadata Policy on Information Management; related directives Requirements, roles and responsibilities for: Creating, managing and monitoring content and metadata standards Requirements, roles and responsibilities for: Creating statistical metadata to support survey and statistical programs High-level governance, roles and responsibilities for designing, creating and maintaining statistical metadata Directive on Informing Respondents Policy on Microdata Access Policy on the review and testing of questionnaires 12

13. Lessons learned  Partnership between business managers and enterprise architects is critical  Cultural issues and has necessitated that we take a federated approach to metadata management  It is important to get the business requirements as well as the IT requirements for metadata systems  Governance, policy instruments and training are needed for transforming the way we do business  Communication and engagement helps to “pave the way” 13

14. Thanks 14